{
"opencollection": "1.0.0",
"info": {
"name": "Girder REST API (Emory Digital Slide Archive) annotation slicer_cli_web API",
"version": "3.2.14"
},
"items": [
{
"info": {
"name": "slicer_cli_web",
"type": "folder"
},
"items": [
{
"info": {
"name": "List CLIs",
"type": "http"
},
"http": {
"method": "GET",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli",
"params": [
{
"name": "folder",
"value": "",
"type": "query",
"description": "The base folder to look for tasks"
}
]
},
"docs": "List CLIs"
},
{
"info": {
"name": "Rerun Color Deconvolution",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ecf/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image to be deconvolved"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image to be deconvolved"
},
{
"name": "outputStainImageFile_1_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_1: Output Image of Stain 1 (*.tiff)"
},
{
"name": "outputStainImageFile_1",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_1: Output Image of Stain 1 (*.tiff)"
},
{
"name": "outputStainImageFile_2_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_2: Output Image of Stain 2 (*.tiff)"
},
{
"name": "outputStainImageFile_2",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_2: Output Image of Stain 2 (*.tiff)"
},
{
"name": "outputStainImageFile_3_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_3: Output Image of Stain 3 (*.tiff)"
},
{
"name": "outputStainImageFile_3",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_3: Output Image of Stain 3 (*.tiff)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to relate images on source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to relate images on source (*.anot)"
},
{
"name": "maxRegionSize",
"value": "",
"type": "query",
"description": "Maximum width and height allowed when processing an image, in order to prevent accidentally running on too large a region. Use -1 for no limit"
},
{
"name": "region",
"value": "",
"type": "query",
"description": "left,top,width,height of the region of interest. All -1 means the whole image is used. as JSON (region)"
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
}
]
},
"docs": "Rerun a previous job: Description:
Unmixes the stains of a composite image given the stain colors
Version: 0.2.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Color Deconvolution",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ecf/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image to be deconvolved"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image to be deconvolved"
},
{
"name": "outputStainImageFile_1_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_1: Output Image of Stain 1 (*.tiff)"
},
{
"name": "outputStainImageFile_1",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_1: Output Image of Stain 1 (*.tiff)"
},
{
"name": "outputStainImageFile_2_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_2: Output Image of Stain 2 (*.tiff)"
},
{
"name": "outputStainImageFile_2",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_2: Output Image of Stain 2 (*.tiff)"
},
{
"name": "outputStainImageFile_3_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_3: Output Image of Stain 3 (*.tiff)"
},
{
"name": "outputStainImageFile_3",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_3: Output Image of Stain 3 (*.tiff)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to relate images on source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to relate images on source (*.anot)"
},
{
"name": "maxRegionSize",
"value": "",
"type": "query",
"description": "Maximum width and height allowed when processing an image, in order to prevent accidentally running on too large a region. Use -1 for no limit"
},
{
"name": "region",
"value": "",
"type": "query",
"description": "left,top,width,height of the region of interest. All -1 means the whole image is used. as JSON (region)"
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
}
]
},
"docs": "Description:
Unmixes the stains of a composite image given the stain colors
Version: 0.2.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Adaptive Color Deconvolution",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed1/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "sample_slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - sample_slide_path: Input image to be deconvolved"
},
{
"name": "sample_slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - sample_slide_path: Input image to be deconvolved"
},
{
"name": "snmf_I_0",
"value": "",
"type": "query",
"description": "Background intensity in each channel as JSON (double-vector)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "snmf_beta",
"value": "",
"type": "query",
"description": "A parameter to control sparsity of stain concentrations"
},
{
"name": "sample_magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling. The default value indicates native scan magnification."
},
{
"name": "sample_min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to\n be sampled from."
},
{
"name": "sample_sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "dask_scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "sample_tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "stains_stain_1",
"value": "",
"type": "query",
"description": "Name for initial estimate of color of stain-1"
},
{
"name": "stains_stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for initial estimate of stain-1 as JSON (double-vector)"
},
{
"name": "stains_stain_2",
"value": "",
"type": "query",
"description": "Name for initial estimate of color of stain-2"
},
{
"name": "stains_stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for initial estimate of stain-2 as JSON (double-vector)"
},
{
"name": "sample_tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Rerun a previous job: Description:
Use sparse non-negative matrix factorization to adaptively deconvolve a given RGB image into intensity images representing distinct stains.
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Adaptive Color Deconvolution",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed1/run",
"params": [
{
"name": "sample_slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - sample_slide_path: Input image to be deconvolved"
},
{
"name": "sample_slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - sample_slide_path: Input image to be deconvolved"
},
{
"name": "snmf_I_0",
"value": "",
"type": "query",
"description": "Background intensity in each channel as JSON (double-vector)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "snmf_beta",
"value": "",
"type": "query",
"description": "A parameter to control sparsity of stain concentrations"
},
{
"name": "sample_magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling. The default value indicates native scan magnification."
},
{
"name": "sample_min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to\n be sampled from."
},
{
"name": "sample_sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "dask_scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "sample_tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "stains_stain_1",
"value": "",
"type": "query",
"description": "Name for initial estimate of color of stain-1"
},
{
"name": "stains_stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for initial estimate of stain-1 as JSON (double-vector)"
},
{
"name": "stains_stain_2",
"value": "",
"type": "query",
"description": "Name for initial estimate of color of stain-2"
},
{
"name": "stains_stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for initial estimate of stain-2 as JSON (double-vector)"
},
{
"name": "sample_tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Description:
Use sparse non-negative matrix factorization to adaptively deconvolve a given RGB image into intensity images representing distinct stains.
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Detects Nuclei",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed3/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "analysis_mag",
"value": "",
"type": "query",
"description": "The magnification at which the analysis should be performed."
},
{
"name": "analysis_roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be done. Must be a four element vector in the format \"left, top, width, height\" in the space of the base layer. Default value of \"-1, -1, -1, -1\" indicates that the whole image should be processed. as JSON (region)"
},
{
"name": "analysis_tile_size",
"value": "",
"type": "query",
"description": "Tile size for blockwise analysis"
},
{
"name": "foreground_threshold",
"value": "",
"type": "query",
"description": "Intensity value to use as threshold to segment foreground in nuclear stain image"
},
{
"name": "frame",
"value": "",
"type": "query",
"description": "Frame index in a multi-frame image"
},
{
"name": "ignore_border_nuclei",
"value": "",
"type": "query",
"description": "Ignore/drop nuclei touching the image/tile border"
},
{
"name": "ImageInversionForm",
"value": "",
"type": "query",
"description": "Image inversion may be needed for greyscale images with bright nuclei and dark background. default option will automatically invert the image if it is single channel. Choose if color inversion is needed."
},
{
"name": "local_max_search_radius",
"value": "",
"type": "query",
"description": "Local max search radius used for detection seed points in nuclei"
},
{
"name": "max_radius",
"value": "",
"type": "query",
"description": "Maximum nuclear radius (used to set max sigma of the multiscale LoG filter)"
},
{
"name": "min_fgnd_frac",
"value": "",
"type": "query",
"description": "The minimum amount of foreground that must be present in a tile for it to be analyzed"
},
{
"name": "min_nucleus_area",
"value": "",
"type": "query",
"description": "Minimum area that each nucleus should have"
},
{
"name": "min_radius",
"value": "",
"type": "query",
"description": "Minimum nuclear radius (used to set min sigma of the multiscale LoG filter)"
},
{
"name": "nuclei_annotation_format",
"value": "",
"type": "query",
"description": "Format of the output nuclei annotations"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "reference_mu_lab",
"value": "",
"type": "query",
"description": "Mean of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "reference_std_lab",
"value": "",
"type": "query",
"description": "Standard deviation of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "remove_overlapping_nuclei_segmentation",
"value": "",
"type": "query",
"description": "Remove overlapping nuclei segmentation from the given region. It is recommended to use this approach when defining the tile overlap parameter."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
},
{
"name": "style",
"value": "",
"type": "query",
"description": "Image style options for compositing a multi-frame image"
},
{
"name": "tile_overlap_value",
"value": "",
"type": "query",
"description": "Tile overlap size in pixels, Default value of -1 indicate that the tile overlap will be set to (max_radius + 1) * 4"
}
]
},
"docs": "Rerun a previous job: Description:
Detects nuclei in a whole-slide image
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Detects Nuclei",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed3/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "analysis_mag",
"value": "",
"type": "query",
"description": "The magnification at which the analysis should be performed."
},
{
"name": "analysis_roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be done. Must be a four element vector in the format \"left, top, width, height\" in the space of the base layer. Default value of \"-1, -1, -1, -1\" indicates that the whole image should be processed. as JSON (region)"
},
{
"name": "analysis_tile_size",
"value": "",
"type": "query",
"description": "Tile size for blockwise analysis"
},
{
"name": "foreground_threshold",
"value": "",
"type": "query",
"description": "Intensity value to use as threshold to segment foreground in nuclear stain image"
},
{
"name": "frame",
"value": "",
"type": "query",
"description": "Frame index in a multi-frame image"
},
{
"name": "ignore_border_nuclei",
"value": "",
"type": "query",
"description": "Ignore/drop nuclei touching the image/tile border"
},
{
"name": "ImageInversionForm",
"value": "",
"type": "query",
"description": "Image inversion may be needed for greyscale images with bright nuclei and dark background. default option will automatically invert the image if it is single channel. Choose if color inversion is needed."
},
{
"name": "local_max_search_radius",
"value": "",
"type": "query",
"description": "Local max search radius used for detection seed points in nuclei"
},
{
"name": "max_radius",
"value": "",
"type": "query",
"description": "Maximum nuclear radius (used to set max sigma of the multiscale LoG filter)"
},
{
"name": "min_fgnd_frac",
"value": "",
"type": "query",
"description": "The minimum amount of foreground that must be present in a tile for it to be analyzed"
},
{
"name": "min_nucleus_area",
"value": "",
"type": "query",
"description": "Minimum area that each nucleus should have"
},
{
"name": "min_radius",
"value": "",
"type": "query",
"description": "Minimum nuclear radius (used to set min sigma of the multiscale LoG filter)"
},
{
"name": "nuclei_annotation_format",
"value": "",
"type": "query",
"description": "Format of the output nuclei annotations"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "reference_mu_lab",
"value": "",
"type": "query",
"description": "Mean of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "reference_std_lab",
"value": "",
"type": "query",
"description": "Standard deviation of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "remove_overlapping_nuclei_segmentation",
"value": "",
"type": "query",
"description": "Remove overlapping nuclei segmentation from the given region. It is recommended to use this approach when defining the tile overlap parameter."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
},
{
"name": "style",
"value": "",
"type": "query",
"description": "Image style options for compositing a multi-frame image"
},
{
"name": "tile_overlap_value",
"value": "",
"type": "query",
"description": "Tile overlap size in pixels, Default value of -1 indicate that the tile overlap will be set to (max_radius + 1) * 4"
}
]
},
"docs": "Description:
Detects nuclei in a whole-slide image
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Computes Nuclei Features",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed5/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image"
},
{
"name": "outputNucleiFeatureFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiFeatureFile: Output nuclei feature file (*.csv or *.h5)"
},
{
"name": "outputNucleiFeatureFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiFeatureFile: Output nuclei feature file (*.csv or *.h5)"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "analysis_mag",
"value": "",
"type": "query",
"description": "The magnification at which the analysis should be performed."
},
{
"name": "analysis_roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be done. Must be a four element vector in the format \"left, top, width, height\" in the space of the base layer. Default value of \"-1, -1, -1, -1\" indicates that the whole image should be processed. as JSON (region)"
},
{
"name": "analysis_tile_size",
"value": "",
"type": "query",
"description": "Tile size for blockwise analysis"
},
{
"name": "cyto_width",
"value": "",
"type": "query",
"description": "Width of ring-like neighborhood region around each nucleus to be considered as cytoplasm"
},
{
"name": "cytoplasm_features",
"value": "",
"type": "query",
"description": "Compute Intensity and Gradient features from the cytoplasm channel"
},
{
"name": "foreground_threshold",
"value": "",
"type": "query",
"description": "Intensity value to use as threshold to segment foreground in nuclear stain image"
},
{
"name": "fsd_features",
"value": "",
"type": "query",
"description": "Compute Fourier Shape Descriptor Features"
},
{
"name": "fsd_bnd_pts",
"value": "",
"type": "query",
"description": "Number of boundary points for computing FSD features"
},
{
"name": "fsd_freq_bins",
"value": "",
"type": "query",
"description": "Number of frequency bins for calculating FSD features"
},
{
"name": "gradient_features",
"value": "",
"type": "query",
"description": "Compute Gradient/Edge Features"
},
{
"name": "haralick_features",
"value": "",
"type": "query",
"description": "Compute Haralick Texture Features"
},
{
"name": "ignore_border_nuclei",
"value": "",
"type": "query",
"description": "Ignore/drop nuclei touching the image/tile border"
},
{
"name": "in_annotations",
"value": "",
"type": "query",
"description": "A comma-separated list of column titles to include in the user attributes of output annotation elements. Blank for none"
},
{
"name": "intensity_features",
"value": "",
"type": "query",
"description": "Compute Intensity Features"
},
{
"name": "local_max_search_radius",
"value": "",
"type": "query",
"description": "Local max search radius used for detection seed points in nuclei"
},
{
"name": "max_radius",
"value": "",
"type": "query",
"description": "Maximum nuclear radius (used to set max sigma of the multiscale LoG filter)"
},
{
"name": "min_fgnd_frac",
"value": "",
"type": "query",
"description": "The minimum amount of foreground that must be present in a tile for it to be analyzed"
},
{
"name": "min_nucleus_area",
"value": "",
"type": "query",
"description": "Minimum area that each nucleus should have"
},
{
"name": "min_radius",
"value": "",
"type": "query",
"description": "Minimum nuclear radius (used to set min sigma of the multiscale LoG filter)"
},
{
"name": "morphometry_features",
"value": "",
"type": "query",
"description": "Compute Morphometry (Size and Shape) Features"
},
{
"name": "nuclei_annotation_format",
"value": "",
"type": "query",
"description": "Format of the output nuclei annotations"
},
{
"name": "num_glcm_levels",
"value": "",
"type": "query",
"description": "Number of GLCM intensity levels (used to compute haralick features)"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "reference_mu_lab",
"value": "",
"type": "query",
"description": "Mean of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "reference_std_lab",
"value": "",
"type": "query",
"description": "Standard deviation of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "remove_overlapping_nuclei_segmentation",
"value": "",
"type": "query",
"description": "Remove overlapping nuclei segmentation from the given region. It is recommended to use this approach when defining the tile overlap parameter."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of the dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a cluster on the local machine"
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
},
{
"name": "tile_overlap_value",
"value": "",
"type": "query",
"description": "Tile overlap size in pixels, Default value of -1 indicate that the tile overlap will be set to (max_radius + 1) * 4"
}
]
},
"docs": "Rerun a previous job: Description:
Computes features for nuclei classification
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Sanghoon Lee (Emory University)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Computes Nuclei Features",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed5/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image"
},
{
"name": "outputNucleiFeatureFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiFeatureFile: Output nuclei feature file (*.csv or *.h5)"
},
{
"name": "outputNucleiFeatureFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiFeatureFile: Output nuclei feature file (*.csv or *.h5)"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "analysis_mag",
"value": "",
"type": "query",
"description": "The magnification at which the analysis should be performed."
},
{
"name": "analysis_roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be done. Must be a four element vector in the format \"left, top, width, height\" in the space of the base layer. Default value of \"-1, -1, -1, -1\" indicates that the whole image should be processed. as JSON (region)"
},
{
"name": "analysis_tile_size",
"value": "",
"type": "query",
"description": "Tile size for blockwise analysis"
},
{
"name": "cyto_width",
"value": "",
"type": "query",
"description": "Width of ring-like neighborhood region around each nucleus to be considered as cytoplasm"
},
{
"name": "cytoplasm_features",
"value": "",
"type": "query",
"description": "Compute Intensity and Gradient features from the cytoplasm channel"
},
{
"name": "foreground_threshold",
"value": "",
"type": "query",
"description": "Intensity value to use as threshold to segment foreground in nuclear stain image"
},
{
"name": "fsd_features",
"value": "",
"type": "query",
"description": "Compute Fourier Shape Descriptor Features"
},
{
"name": "fsd_bnd_pts",
"value": "",
"type": "query",
"description": "Number of boundary points for computing FSD features"
},
{
"name": "fsd_freq_bins",
"value": "",
"type": "query",
"description": "Number of frequency bins for calculating FSD features"
},
{
"name": "gradient_features",
"value": "",
"type": "query",
"description": "Compute Gradient/Edge Features"
},
{
"name": "haralick_features",
"value": "",
"type": "query",
"description": "Compute Haralick Texture Features"
},
{
"name": "ignore_border_nuclei",
"value": "",
"type": "query",
"description": "Ignore/drop nuclei touching the image/tile border"
},
{
"name": "in_annotations",
"value": "",
"type": "query",
"description": "A comma-separated list of column titles to include in the user attributes of output annotation elements. Blank for none"
},
{
"name": "intensity_features",
"value": "",
"type": "query",
"description": "Compute Intensity Features"
},
{
"name": "local_max_search_radius",
"value": "",
"type": "query",
"description": "Local max search radius used for detection seed points in nuclei"
},
{
"name": "max_radius",
"value": "",
"type": "query",
"description": "Maximum nuclear radius (used to set max sigma of the multiscale LoG filter)"
},
{
"name": "min_fgnd_frac",
"value": "",
"type": "query",
"description": "The minimum amount of foreground that must be present in a tile for it to be analyzed"
},
{
"name": "min_nucleus_area",
"value": "",
"type": "query",
"description": "Minimum area that each nucleus should have"
},
{
"name": "min_radius",
"value": "",
"type": "query",
"description": "Minimum nuclear radius (used to set min sigma of the multiscale LoG filter)"
},
{
"name": "morphometry_features",
"value": "",
"type": "query",
"description": "Compute Morphometry (Size and Shape) Features"
},
{
"name": "nuclei_annotation_format",
"value": "",
"type": "query",
"description": "Format of the output nuclei annotations"
},
{
"name": "num_glcm_levels",
"value": "",
"type": "query",
"description": "Number of GLCM intensity levels (used to compute haralick features)"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "reference_mu_lab",
"value": "",
"type": "query",
"description": "Mean of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "reference_std_lab",
"value": "",
"type": "query",
"description": "Standard deviation of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "remove_overlapping_nuclei_segmentation",
"value": "",
"type": "query",
"description": "Remove overlapping nuclei segmentation from the given region. It is recommended to use this approach when defining the tile overlap parameter."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of the dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a cluster on the local machine"
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
},
{
"name": "tile_overlap_value",
"value": "",
"type": "query",
"description": "Tile overlap size in pixels, Default value of -1 indicate that the tile overlap will be set to (max_radius + 1) * 4"
}
]
},
"docs": "Description:
Computes features for nuclei classification
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Sanghoon Lee (Emory University)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Classify Nuclei",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed7/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image file"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image file"
},
{
"name": "inputModelFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputModelFile: Pickled file (*.pkl) of the scikit-learn model for classifying nuclei"
},
{
"name": "inputModelFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputModelFile: Pickled file (*.pkl) of the scikit-learn model for classifying nuclei"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot) with the same nuclei in input nuclei annotation file if provided) with nuclei sorted into groups based on class and accompanied by heatmaps of the classification probabilities"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot) with the same nuclei in input nuclei annotation file if provided) with nuclei sorted into groups based on class and accompanied by heatmaps of the classification probabilities"
},
{
"name": "inputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputNucleiAnnotationFile: Input nuclei annotation file (*.anot) containing nuclei annotations in the same order as their features in the feature file"
},
{
"name": "inputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputNucleiAnnotationFile: Input nuclei annotation file (*.anot) containing nuclei annotations in the same order as their features in the feature file"
},
{
"name": "inputNucleiFeatureFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputNucleiFeatureFile: Input nuclei feature file (*.csv, *.h5) containing the features of all nuclei to be classified"
},
{
"name": "inputNucleiFeatureFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputNucleiFeatureFile: Input nuclei feature file (*.csv, *.h5) containing the features of all nuclei to be classified"
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
}
]
},
"docs": "Rerun a previous job: Description:
Classify nuclei in an image based on pre-computed features
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware), Subin Erattakulangara (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Classify Nuclei",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed7/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image file"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image file"
},
{
"name": "inputModelFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputModelFile: Pickled file (*.pkl) of the scikit-learn model for classifying nuclei"
},
{
"name": "inputModelFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputModelFile: Pickled file (*.pkl) of the scikit-learn model for classifying nuclei"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot) with the same nuclei in input nuclei annotation file if provided) with nuclei sorted into groups based on class and accompanied by heatmaps of the classification probabilities"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot) with the same nuclei in input nuclei annotation file if provided) with nuclei sorted into groups based on class and accompanied by heatmaps of the classification probabilities"
},
{
"name": "inputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputNucleiAnnotationFile: Input nuclei annotation file (*.anot) containing nuclei annotations in the same order as their features in the feature file"
},
{
"name": "inputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputNucleiAnnotationFile: Input nuclei annotation file (*.anot) containing nuclei annotations in the same order as their features in the feature file"
},
{
"name": "inputNucleiFeatureFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputNucleiFeatureFile: Input nuclei feature file (*.csv, *.h5) containing the features of all nuclei to be classified"
},
{
"name": "inputNucleiFeatureFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputNucleiFeatureFile: Input nuclei feature file (*.csv, *.h5) containing the features of all nuclei to be classified"
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
}
]
},
"docs": "Description:
Classify nuclei in an image based on pre-computed features
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware), Subin Erattakulangara (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Compute Background Intensity",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed9/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - slide_path: Path to input slide image to be deconvolved"
},
{
"name": "slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - slide_path: Path to input slide image to be deconvolved"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output intensity in SDA space (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output intensity in SDA space (*.anot)"
},
{
"name": "magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling."
},
{
"name": "min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to be sampled from."
},
{
"name": "sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Rerun a previous job: Description:
Sample the background of a slide to compute the median background intensity.
Version: 0.1.0
License: Apache 2.0
Author(s): Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Compute Background Intensity",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566ed9/run",
"params": [
{
"name": "slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - slide_path: Path to input slide image to be deconvolved"
},
{
"name": "slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - slide_path: Path to input slide image to be deconvolved"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output intensity in SDA space (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output intensity in SDA space (*.anot)"
},
{
"name": "magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling."
},
{
"name": "min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to be sampled from."
},
{
"name": "sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Description:
Sample the background of a slide to compute the median background intensity.
Version: 0.1.0
License: Apache 2.0
Author(s): Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Separate Stains (PCA-based Macenko method)",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566edb/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "sample_slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - sample_slide_path: Path to input slide image to be deconvolved"
},
{
"name": "sample_slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - sample_slide_path: Path to input slide image to be deconvolved"
},
{
"name": "macenko_I_0",
"value": "",
"type": "query",
"description": "Background intensity in each channel as JSON (double-vector)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "sample_magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling. The default value indicates native scan magnification."
},
{
"name": "macenko_max_angle_percentile",
"value": "",
"type": "query",
"description": "The larger percentile of one of the vectors to pick from the angle distribution"
},
{
"name": "macenko_min_angle_percentile",
"value": "",
"type": "query",
"description": "The smaller percentile of one of the vectors to pick from the angle distribution"
},
{
"name": "sample_min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to\n be sampled from."
},
{
"name": "macenko_minimum_magnitude",
"value": "",
"type": "query",
"description": "The magnitude below which vectors will be excluded from the computation of the angle distribution"
},
{
"name": "sample_sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "dask_scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "sample_tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "sample_tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Rerun a previous job: Description:
Sample the foreground of a slide to compute the stain vectors using the Macenko method.
Version: 0.1.0
License: Apache 2.0
Author(s): Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Separate Stains (PCA-based Macenko method)",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566edb/run",
"params": [
{
"name": "sample_slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - sample_slide_path: Path to input slide image to be deconvolved"
},
{
"name": "sample_slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - sample_slide_path: Path to input slide image to be deconvolved"
},
{
"name": "macenko_I_0",
"value": "",
"type": "query",
"description": "Background intensity in each channel as JSON (double-vector)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "sample_magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling. The default value indicates native scan magnification."
},
{
"name": "macenko_max_angle_percentile",
"value": "",
"type": "query",
"description": "The larger percentile of one of the vectors to pick from the angle distribution"
},
{
"name": "macenko_min_angle_percentile",
"value": "",
"type": "query",
"description": "The smaller percentile of one of the vectors to pick from the angle distribution"
},
{
"name": "sample_min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to\n be sampled from."
},
{
"name": "macenko_minimum_magnitude",
"value": "",
"type": "query",
"description": "The magnitude below which vectors will be excluded from the computation of the angle distribution"
},
{
"name": "sample_sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "dask_scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "sample_tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "sample_tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Description:
Sample the foreground of a slide to compute the stain vectors using the Macenko method.
Version: 0.1.0
License: Apache 2.0
Author(s): Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Positive Pixel Count",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566edd/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image in which to count and classify positive pixels"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image in which to count and classify positive pixels"
},
{
"name": "hue_value",
"value": "",
"type": "query",
"description": "Center of the hue range in HSI space for the positive color, in the range [0, 1]"
},
{
"name": "hue_width",
"value": "",
"type": "query",
"description": "Width of the hue range in HSI space"
},
{
"name": "saturation_minimum",
"value": "",
"type": "query",
"description": "Minimum saturation of positive pixels in HSI space, in the range [0, 1]"
},
{
"name": "intensity_upper_limit",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space above which a pixel is considered negative, in the range [0, 1]"
},
{
"name": "intensity_weak_threshold",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space that separates weak-positive pixels (above) from plain positive pixels (below)"
},
{
"name": "intensity_strong_threshold",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space that separates plain positive pixels (above) from strong positive pixels (below)"
},
{
"name": "intensity_lower_limit",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space below which a pixel is considered negative"
},
{
"name": "frame",
"value": "",
"type": "query",
"description": "Frame index in a multi-frame image"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to relate the image to the source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to relate the image to the source (*.anot)"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "outputLabelImage_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputLabelImage: Color-coded image of the region, showing the various classes of pixel"
},
{
"name": "outputLabelImage",
"value": "",
"type": "query",
"description": "Name of output image - outputLabelImage: Color-coded image of the region, showing the various classes of pixel"
},
{
"name": "outputImageForm",
"value": "",
"type": "query",
"description": "The output image can either be colored for easy visibility or coded as categorical values where 0 is negative, 1 weak, 2 plain, and 3 strong"
},
{
"name": "region",
"value": "",
"type": "query",
"description": "Region of interest where analysis is performed. This is either -1,-1,-1,-1 for the whole image, or a four-element vector in the format \"left, top, width, height\", or a list of four or more x,y vertices to specify a polygon. as JSON (region)"
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "style",
"value": "",
"type": "query",
"description": "Image style options for compositing a multi-frame image"
}
]
},
"docs": "Rerun a previous job: Description:
Counts different types of positive pixels based on values in the HSI color space
Version: 0.1.0
License: Apache 2.0
Author(s): David Manthey (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Positive Pixel Count",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/5f3d811c50cd9fe632566edd/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image in which to count and classify positive pixels"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image in which to count and classify positive pixels"
},
{
"name": "hue_value",
"value": "",
"type": "query",
"description": "Center of the hue range in HSI space for the positive color, in the range [0, 1]"
},
{
"name": "hue_width",
"value": "",
"type": "query",
"description": "Width of the hue range in HSI space"
},
{
"name": "saturation_minimum",
"value": "",
"type": "query",
"description": "Minimum saturation of positive pixels in HSI space, in the range [0, 1]"
},
{
"name": "intensity_upper_limit",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space above which a pixel is considered negative, in the range [0, 1]"
},
{
"name": "intensity_weak_threshold",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space that separates weak-positive pixels (above) from plain positive pixels (below)"
},
{
"name": "intensity_strong_threshold",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space that separates plain positive pixels (above) from strong positive pixels (below)"
},
{
"name": "intensity_lower_limit",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space below which a pixel is considered negative"
},
{
"name": "frame",
"value": "",
"type": "query",
"description": "Frame index in a multi-frame image"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to relate the image to the source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to relate the image to the source (*.anot)"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "outputLabelImage_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputLabelImage: Color-coded image of the region, showing the various classes of pixel"
},
{
"name": "outputLabelImage",
"value": "",
"type": "query",
"description": "Name of output image - outputLabelImage: Color-coded image of the region, showing the various classes of pixel"
},
{
"name": "outputImageForm",
"value": "",
"type": "query",
"description": "The output image can either be colored for easy visibility or coded as categorical values where 0 is negative, 1 weak, 2 plain, and 3 strong"
},
{
"name": "region",
"value": "",
"type": "query",
"description": "Region of interest where analysis is performed. This is either -1,-1,-1,-1 for the whole image, or a four-element vector in the format \"left, top, width, height\", or a list of four or more x,y vertices to specify a polygon. as JSON (region)"
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "style",
"value": "",
"type": "query",
"description": "Image style options for compositing a multi-frame image"
}
]
},
"docs": "Description:
Counts different types of positive pixels based on values in the HSI color space
Version: 0.1.0
License: Apache 2.0
Author(s): David Manthey (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Superpixel Pixelmap",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/6226c700ea96453654b57afd/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image for superpixel segmentation"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image for superpixel segmentation"
},
{
"name": "outputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputImageFile: Output Image of Superpixel Pixelmap (*.tiff)"
},
{
"name": "outputImageFile",
"value": "",
"type": "query",
"description": "Name of output image - outputImageFile: Output Image of Superpixel Pixelmap (*.tiff)"
},
{
"name": "boundaries",
"value": "",
"type": "query",
"description": "Mark the boundary around each superpixel. Boundaries are specified with a separate pixelmap index value that is always 1 higher than the pixelmap index value of the superpixel's interior."
},
{
"name": "bounding",
"value": "",
"type": "query",
"description": "If specified, output an annotation with the bounding box of each superpixel. Internal adds a user.bbox field as a single array to the superpixel annotation with the base image coordinates left,top,right,bottom for each superpixel."
},
{
"name": "compactness",
"value": "",
"type": "query",
"description": "Balances color proximity and space proximity. Higher values give more weight to space proximity, making superpixel shapes more square/cubic."
},
{
"name": "default_category_label",
"value": "",
"type": "query",
"description": "Default category label used for superpixels"
},
{
"name": "default_fillColor",
"value": "",
"type": "query",
"description": "Default color for superpixels"
},
{
"name": "default_strokeColor",
"value": "",
"type": "query",
"description": "If creating boundary superpixels, this is the default color of the boundaries of the superpixels"
},
{
"name": "magnification",
"value": "",
"type": "query",
"description": "If specified, the magnification that should be used for the superpixels. If 0, the base magnfication is used"
},
{
"name": "overlap",
"value": "",
"type": "query",
"description": "If specified, overlap tile computation to avoid edge effects."
},
{
"name": "roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be run as JSON (region)"
},
{
"name": "sigma",
"value": "",
"type": "query",
"description": "Width of Gaussian smoothing kernel for pre-processing for each dimension of the image. The same sigma is applied to each dimension in case of a scalar value. Zero means no smoothing."
},
{
"name": "slic_zero",
"value": "",
"type": "query",
"description": "If true, run the algorithm in SLIC0 mode to adaptively determine compactness for each superpixel."
},
{
"name": "superpixelSize",
"value": "",
"type": "query",
"description": "Approximate diameter of the average superpixel."
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to display pixelmap on source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to display pixelmap on source (*.anot)"
},
{
"name": "tileSize",
"value": "",
"type": "query",
"description": "Specify the size of the working tile. If there is no overlap, superpixel boundaries will appear at these locations."
}
]
},
"docs": "Rerun a previous job: Description:
Create a pixelmap image of superpixels using SLIC.
Version: 0.1.0
License: Apache 2.0
Author(s): Kitware
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Superpixel Pixelmap",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/6226c700ea96453654b57afd/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image for superpixel segmentation"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image for superpixel segmentation"
},
{
"name": "outputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputImageFile: Output Image of Superpixel Pixelmap (*.tiff)"
},
{
"name": "outputImageFile",
"value": "",
"type": "query",
"description": "Name of output image - outputImageFile: Output Image of Superpixel Pixelmap (*.tiff)"
},
{
"name": "boundaries",
"value": "",
"type": "query",
"description": "Mark the boundary around each superpixel. Boundaries are specified with a separate pixelmap index value that is always 1 higher than the pixelmap index value of the superpixel's interior."
},
{
"name": "bounding",
"value": "",
"type": "query",
"description": "If specified, output an annotation with the bounding box of each superpixel. Internal adds a user.bbox field as a single array to the superpixel annotation with the base image coordinates left,top,right,bottom for each superpixel."
},
{
"name": "compactness",
"value": "",
"type": "query",
"description": "Balances color proximity and space proximity. Higher values give more weight to space proximity, making superpixel shapes more square/cubic."
},
{
"name": "default_category_label",
"value": "",
"type": "query",
"description": "Default category label used for superpixels"
},
{
"name": "default_fillColor",
"value": "",
"type": "query",
"description": "Default color for superpixels"
},
{
"name": "default_strokeColor",
"value": "",
"type": "query",
"description": "If creating boundary superpixels, this is the default color of the boundaries of the superpixels"
},
{
"name": "magnification",
"value": "",
"type": "query",
"description": "If specified, the magnification that should be used for the superpixels. If 0, the base magnfication is used"
},
{
"name": "overlap",
"value": "",
"type": "query",
"description": "If specified, overlap tile computation to avoid edge effects."
},
{
"name": "roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be run as JSON (region)"
},
{
"name": "sigma",
"value": "",
"type": "query",
"description": "Width of Gaussian smoothing kernel for pre-processing for each dimension of the image. The same sigma is applied to each dimension in case of a scalar value. Zero means no smoothing."
},
{
"name": "slic_zero",
"value": "",
"type": "query",
"description": "If true, run the algorithm in SLIC0 mode to adaptively determine compactness for each superpixel."
},
{
"name": "superpixelSize",
"value": "",
"type": "query",
"description": "Approximate diameter of the average superpixel."
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to display pixelmap on source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to display pixelmap on source (*.anot)"
},
{
"name": "tileSize",
"value": "",
"type": "query",
"description": "Specify the size of the working tile. If there is no overlap, superpixel boundaries will appear at these locations."
}
]
},
"docs": "Description:
Create a pixelmap image of superpixels using SLIC.
Version: 0.1.0
License: Apache 2.0
Author(s): Kitware
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Simple Get Region",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/63a0a1fd9a9ebb3f668acd34/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "in_file",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - in_file: Input image"
},
{
"name": "in_file_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - in_file: Input image"
},
{
"name": "mag",
"value": "",
"type": "query",
"description": "Output thumbnail magnification"
},
{
"name": "out_file_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - out_file: Output Region Image file"
},
{
"name": "out_file",
"value": "",
"type": "query",
"description": "Name of output image - out_file: Output Region Image file"
},
{
"name": "girderApiUrl",
"value": "",
"type": "query",
"description": "A Girder API URL (e.g., https://girder.example.com:443/api/v1)"
},
{
"name": "girderToken",
"value": "",
"type": "query",
"description": "A Girder token"
}
]
},
"docs": "Rerun a previous job: Description:
Simple Get Region
Version: 0.1.0
License: Apache 2.0
Author(s): David Gutman and Jc Vizcarra"
},
{
"info": {
"name": "Simple Get Region",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/63a0a1fd9a9ebb3f668acd34/run",
"params": [
{
"name": "in_file",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - in_file: Input image"
},
{
"name": "in_file_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - in_file: Input image"
},
{
"name": "mag",
"value": "",
"type": "query",
"description": "Output thumbnail magnification"
},
{
"name": "out_file_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - out_file: Output Region Image file"
},
{
"name": "out_file",
"value": "",
"type": "query",
"description": "Name of output image - out_file: Output Region Image file"
},
{
"name": "girderApiUrl",
"value": "",
"type": "query",
"description": "A Girder API URL (e.g., https://girder.example.com:443/api/v1)"
},
{
"name": "girderToken",
"value": "",
"type": "query",
"description": "A Girder token"
}
]
},
"docs": "Description:
Simple Get Region
Version: 0.1.0
License: Apache 2.0
Author(s): David Gutman and Jc Vizcarra"
},
{
"info": {
"name": "Get a specific CLI",
"type": "http"
},
"http": {
"method": "GET",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/:id",
"params": [
{
"name": "id",
"value": "",
"type": "path",
"description": "The task item"
}
]
},
"docs": "Get a specific CLI"
},
{
"info": {
"name": "Get a specific CLI",
"type": "http"
},
"http": {
"method": "DELETE",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/:id",
"params": [
{
"name": "id",
"value": "",
"type": "path",
"description": "The task item"
}
]
},
"docs": "Get a specific CLI"
},
{
"info": {
"name": "Get a specific CLI",
"type": "http"
},
"http": {
"method": "GET",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/cli/:id/xml",
"params": [
{
"name": "id",
"value": "",
"type": "path",
"description": "The task item"
}
]
},
"docs": "Get a specific CLI"
},
{
"info": {
"name": "List docker images and their CLIs",
"type": "http"
},
"http": {
"method": "GET",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/docker_image"
},
"docs": "You must be logged in to see any results."
},
{
"info": {
"name": "Add one or a list of images",
"type": "http"
},
"http": {
"method": "PUT",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/docker_image",
"params": [
{
"name": "name",
"value": "",
"type": "query",
"description": "A name or a list of names of the docker images to be loaded"
},
{
"name": "folder",
"value": "",
"type": "query",
"description": "The base folder id to upload the tasks to"
},
{
"name": "pull",
"value": "",
"type": "query",
"description": "If True, try to repull all images"
}
]
},
"docs": "Must be a system administrator to call this."
},
{
"info": {
"name": "Remove a docker image",
"type": "http"
},
"http": {
"method": "DELETE",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/docker_image",
"params": [
{
"name": "name",
"value": "",
"type": "query",
"description": "The name or a list of names of the docker images to be removed"
},
{
"name": "delete_from_local_repo",
"value": "",
"type": "query",
"description": "If True the image is deleted from the local repo, requiring it to be pulled from a remote repository the next time it is used. If False the metadata regarding the image is deleted, but the docker image remains."
}
]
},
"docs": "Must be a system administrator to call this."
},
{
"info": {
"name": "Rerun Compute Background Intensity",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/BackgroundIntensity/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - slide_path: Path to input slide image to be deconvolved"
},
{
"name": "slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - slide_path: Path to input slide image to be deconvolved"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output intensity in SDA space (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output intensity in SDA space (*.anot)"
},
{
"name": "magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling."
},
{
"name": "min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to be sampled from."
},
{
"name": "sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Rerun a previous job: Description:
Sample the background of a slide to compute the median background intensity.
Version: 0.1.0
License: Apache 2.0
Author(s): Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Compute Background Intensity",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/BackgroundIntensity/run",
"params": [
{
"name": "slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - slide_path: Path to input slide image to be deconvolved"
},
{
"name": "slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - slide_path: Path to input slide image to be deconvolved"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output intensity in SDA space (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output intensity in SDA space (*.anot)"
},
{
"name": "magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling."
},
{
"name": "min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to be sampled from."
},
{
"name": "sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Description:
Sample the background of a slide to compute the median background intensity.
Version: 0.1.0
License: Apache 2.0
Author(s): Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Color Deconvolution",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/ColorDeconvolution/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image to be deconvolved"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image to be deconvolved"
},
{
"name": "outputStainImageFile_1_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_1: Output Image of Stain 1 (*.tiff)"
},
{
"name": "outputStainImageFile_1",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_1: Output Image of Stain 1 (*.tiff)"
},
{
"name": "outputStainImageFile_2_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_2: Output Image of Stain 2 (*.tiff)"
},
{
"name": "outputStainImageFile_2",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_2: Output Image of Stain 2 (*.tiff)"
},
{
"name": "outputStainImageFile_3_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_3: Output Image of Stain 3 (*.tiff)"
},
{
"name": "outputStainImageFile_3",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_3: Output Image of Stain 3 (*.tiff)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to relate images on source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to relate images on source (*.anot)"
},
{
"name": "maxRegionSize",
"value": "",
"type": "query",
"description": "Maximum width and height allowed when processing an image, in order to prevent accidentally running on too large a region. Use -1 for no limit"
},
{
"name": "region",
"value": "",
"type": "query",
"description": "left,top,width,height of the region of interest. All -1 means the whole image is used. as JSON (region)"
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
}
]
},
"docs": "Rerun a previous job: Description:
Unmixes the stains of a composite image given the stain colors
Version: 0.2.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Color Deconvolution",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/ColorDeconvolution/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image to be deconvolved"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image to be deconvolved"
},
{
"name": "outputStainImageFile_1_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_1: Output Image of Stain 1 (*.tiff)"
},
{
"name": "outputStainImageFile_1",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_1: Output Image of Stain 1 (*.tiff)"
},
{
"name": "outputStainImageFile_2_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_2: Output Image of Stain 2 (*.tiff)"
},
{
"name": "outputStainImageFile_2",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_2: Output Image of Stain 2 (*.tiff)"
},
{
"name": "outputStainImageFile_3_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputStainImageFile_3: Output Image of Stain 3 (*.tiff)"
},
{
"name": "outputStainImageFile_3",
"value": "",
"type": "query",
"description": "Name of output image - outputStainImageFile_3: Output Image of Stain 3 (*.tiff)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to relate images on source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to relate images on source (*.anot)"
},
{
"name": "maxRegionSize",
"value": "",
"type": "query",
"description": "Maximum width and height allowed when processing an image, in order to prevent accidentally running on too large a region. Use -1 for no limit"
},
{
"name": "region",
"value": "",
"type": "query",
"description": "left,top,width,height of the region of interest. All -1 means the whole image is used. as JSON (region)"
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
}
]
},
"docs": "Description:
Unmixes the stains of a composite image given the stain colors
Version: 0.2.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Computes Nuclei Features",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/ComputeNucleiFeatures/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image"
},
{
"name": "outputNucleiFeatureFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiFeatureFile: Output nuclei feature file (*.csv or *.h5)"
},
{
"name": "outputNucleiFeatureFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiFeatureFile: Output nuclei feature file (*.csv or *.h5)"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "analysis_mag",
"value": "",
"type": "query",
"description": "The magnification at which the analysis should be performed."
},
{
"name": "analysis_roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be done. Must be a four element vector in the format \"left, top, width, height\" in the space of the base layer. Default value of \"-1, -1, -1, -1\" indicates that the whole image should be processed. as JSON (region)"
},
{
"name": "analysis_tile_size",
"value": "",
"type": "query",
"description": "Tile size for blockwise analysis"
},
{
"name": "cyto_width",
"value": "",
"type": "query",
"description": "Width of ring-like neighborhood region around each nucleus to be considered as cytoplasm"
},
{
"name": "cytoplasm_features",
"value": "",
"type": "query",
"description": "Compute Intensity and Gradient features from the cytoplasm channel"
},
{
"name": "foreground_threshold",
"value": "",
"type": "query",
"description": "Intensity value to use as threshold to segment foreground in nuclear stain image"
},
{
"name": "fsd_features",
"value": "",
"type": "query",
"description": "Compute Fourier Shape Descriptor Features"
},
{
"name": "fsd_bnd_pts",
"value": "",
"type": "query",
"description": "Number of boundary points for computing FSD features"
},
{
"name": "fsd_freq_bins",
"value": "",
"type": "query",
"description": "Number of frequency bins for calculating FSD features"
},
{
"name": "gradient_features",
"value": "",
"type": "query",
"description": "Compute Gradient/Edge Features"
},
{
"name": "haralick_features",
"value": "",
"type": "query",
"description": "Compute Haralick Texture Features"
},
{
"name": "ignore_border_nuclei",
"value": "",
"type": "query",
"description": "Ignore/drop nuclei touching the image/tile border"
},
{
"name": "in_annotations",
"value": "",
"type": "query",
"description": "A comma-separated list of column titles to include in the user attributes of output annotation elements. Blank for none"
},
{
"name": "intensity_features",
"value": "",
"type": "query",
"description": "Compute Intensity Features"
},
{
"name": "local_max_search_radius",
"value": "",
"type": "query",
"description": "Local max search radius used for detection seed points in nuclei"
},
{
"name": "max_radius",
"value": "",
"type": "query",
"description": "Maximum nuclear radius (used to set max sigma of the multiscale LoG filter)"
},
{
"name": "min_fgnd_frac",
"value": "",
"type": "query",
"description": "The minimum amount of foreground that must be present in a tile for it to be analyzed"
},
{
"name": "min_nucleus_area",
"value": "",
"type": "query",
"description": "Minimum area that each nucleus should have"
},
{
"name": "min_radius",
"value": "",
"type": "query",
"description": "Minimum nuclear radius (used to set min sigma of the multiscale LoG filter)"
},
{
"name": "morphometry_features",
"value": "",
"type": "query",
"description": "Compute Morphometry (Size and Shape) Features"
},
{
"name": "nuclei_annotation_format",
"value": "",
"type": "query",
"description": "Format of the output nuclei annotations"
},
{
"name": "num_glcm_levels",
"value": "",
"type": "query",
"description": "Number of GLCM intensity levels (used to compute haralick features)"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "reference_mu_lab",
"value": "",
"type": "query",
"description": "Mean of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "reference_std_lab",
"value": "",
"type": "query",
"description": "Standard deviation of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "remove_overlapping_nuclei_segmentation",
"value": "",
"type": "query",
"description": "Remove overlapping nuclei segmentation from the given region. It is recommended to use this approach when defining the tile overlap parameter."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of the dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a cluster on the local machine"
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
},
{
"name": "tile_overlap_value",
"value": "",
"type": "query",
"description": "Tile overlap size in pixels, Default value of -1 indicate that the tile overlap will be set to (max_radius + 1) * 4"
}
]
},
"docs": "Rerun a previous job: Description:
Computes features for nuclei classification
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Sanghoon Lee (Emory University)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Computes Nuclei Features",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/ComputeNucleiFeatures/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image"
},
{
"name": "outputNucleiFeatureFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiFeatureFile: Output nuclei feature file (*.csv or *.h5)"
},
{
"name": "outputNucleiFeatureFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiFeatureFile: Output nuclei feature file (*.csv or *.h5)"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "analysis_mag",
"value": "",
"type": "query",
"description": "The magnification at which the analysis should be performed."
},
{
"name": "analysis_roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be done. Must be a four element vector in the format \"left, top, width, height\" in the space of the base layer. Default value of \"-1, -1, -1, -1\" indicates that the whole image should be processed. as JSON (region)"
},
{
"name": "analysis_tile_size",
"value": "",
"type": "query",
"description": "Tile size for blockwise analysis"
},
{
"name": "cyto_width",
"value": "",
"type": "query",
"description": "Width of ring-like neighborhood region around each nucleus to be considered as cytoplasm"
},
{
"name": "cytoplasm_features",
"value": "",
"type": "query",
"description": "Compute Intensity and Gradient features from the cytoplasm channel"
},
{
"name": "foreground_threshold",
"value": "",
"type": "query",
"description": "Intensity value to use as threshold to segment foreground in nuclear stain image"
},
{
"name": "fsd_features",
"value": "",
"type": "query",
"description": "Compute Fourier Shape Descriptor Features"
},
{
"name": "fsd_bnd_pts",
"value": "",
"type": "query",
"description": "Number of boundary points for computing FSD features"
},
{
"name": "fsd_freq_bins",
"value": "",
"type": "query",
"description": "Number of frequency bins for calculating FSD features"
},
{
"name": "gradient_features",
"value": "",
"type": "query",
"description": "Compute Gradient/Edge Features"
},
{
"name": "haralick_features",
"value": "",
"type": "query",
"description": "Compute Haralick Texture Features"
},
{
"name": "ignore_border_nuclei",
"value": "",
"type": "query",
"description": "Ignore/drop nuclei touching the image/tile border"
},
{
"name": "in_annotations",
"value": "",
"type": "query",
"description": "A comma-separated list of column titles to include in the user attributes of output annotation elements. Blank for none"
},
{
"name": "intensity_features",
"value": "",
"type": "query",
"description": "Compute Intensity Features"
},
{
"name": "local_max_search_radius",
"value": "",
"type": "query",
"description": "Local max search radius used for detection seed points in nuclei"
},
{
"name": "max_radius",
"value": "",
"type": "query",
"description": "Maximum nuclear radius (used to set max sigma of the multiscale LoG filter)"
},
{
"name": "min_fgnd_frac",
"value": "",
"type": "query",
"description": "The minimum amount of foreground that must be present in a tile for it to be analyzed"
},
{
"name": "min_nucleus_area",
"value": "",
"type": "query",
"description": "Minimum area that each nucleus should have"
},
{
"name": "min_radius",
"value": "",
"type": "query",
"description": "Minimum nuclear radius (used to set min sigma of the multiscale LoG filter)"
},
{
"name": "morphometry_features",
"value": "",
"type": "query",
"description": "Compute Morphometry (Size and Shape) Features"
},
{
"name": "nuclei_annotation_format",
"value": "",
"type": "query",
"description": "Format of the output nuclei annotations"
},
{
"name": "num_glcm_levels",
"value": "",
"type": "query",
"description": "Number of GLCM intensity levels (used to compute haralick features)"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "reference_mu_lab",
"value": "",
"type": "query",
"description": "Mean of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "reference_std_lab",
"value": "",
"type": "query",
"description": "Standard deviation of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "remove_overlapping_nuclei_segmentation",
"value": "",
"type": "query",
"description": "Remove overlapping nuclei segmentation from the given region. It is recommended to use this approach when defining the tile overlap parameter."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of the dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a cluster on the local machine"
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
},
{
"name": "tile_overlap_value",
"value": "",
"type": "query",
"description": "Tile overlap size in pixels, Default value of -1 indicate that the tile overlap will be set to (max_radius + 1) * 4"
}
]
},
"docs": "Description:
Computes features for nuclei classification
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Sanghoon Lee (Emory University)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Classify Nuclei",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/NucleiClassification/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image file"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image file"
},
{
"name": "inputModelFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputModelFile: Pickled file (*.pkl) of the scikit-learn model for classifying nuclei"
},
{
"name": "inputModelFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputModelFile: Pickled file (*.pkl) of the scikit-learn model for classifying nuclei"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot) with the same nuclei in input nuclei annotation file if provided) with nuclei sorted into groups based on class and accompanied by heatmaps of the classification probabilities"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot) with the same nuclei in input nuclei annotation file if provided) with nuclei sorted into groups based on class and accompanied by heatmaps of the classification probabilities"
},
{
"name": "inputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputNucleiAnnotationFile: Input nuclei annotation file (*.anot) containing nuclei annotations in the same order as their features in the feature file"
},
{
"name": "inputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputNucleiAnnotationFile: Input nuclei annotation file (*.anot) containing nuclei annotations in the same order as their features in the feature file"
},
{
"name": "inputNucleiFeatureFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputNucleiFeatureFile: Input nuclei feature file (*.csv, *.h5) containing the features of all nuclei to be classified"
},
{
"name": "inputNucleiFeatureFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputNucleiFeatureFile: Input nuclei feature file (*.csv, *.h5) containing the features of all nuclei to be classified"
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
}
]
},
"docs": "Rerun a previous job: Description:
Classify nuclei in an image based on pre-computed features
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware), Subin Erattakulangara (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Classify Nuclei",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/NucleiClassification/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image file"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image file"
},
{
"name": "inputModelFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputModelFile: Pickled file (*.pkl) of the scikit-learn model for classifying nuclei"
},
{
"name": "inputModelFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputModelFile: Pickled file (*.pkl) of the scikit-learn model for classifying nuclei"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot) with the same nuclei in input nuclei annotation file if provided) with nuclei sorted into groups based on class and accompanied by heatmaps of the classification probabilities"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot) with the same nuclei in input nuclei annotation file if provided) with nuclei sorted into groups based on class and accompanied by heatmaps of the classification probabilities"
},
{
"name": "inputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputNucleiAnnotationFile: Input nuclei annotation file (*.anot) containing nuclei annotations in the same order as their features in the feature file"
},
{
"name": "inputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputNucleiAnnotationFile: Input nuclei annotation file (*.anot) containing nuclei annotations in the same order as their features in the feature file"
},
{
"name": "inputNucleiFeatureFile",
"value": "",
"type": "query",
"description": "Girder ID of input file (if batch input, this is a regex for item names) - inputNucleiFeatureFile: Input nuclei feature file (*.csv, *.h5) containing the features of all nuclei to be classified"
},
{
"name": "inputNucleiFeatureFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input file - inputNucleiFeatureFile: Input nuclei feature file (*.csv, *.h5) containing the features of all nuclei to be classified"
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
}
]
},
"docs": "Description:
Classify nuclei in an image based on pre-computed features
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware), Subin Erattakulangara (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Detects Nuclei",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/NucleiDetection/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "analysis_mag",
"value": "",
"type": "query",
"description": "The magnification at which the analysis should be performed."
},
{
"name": "analysis_roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be done. Must be a four element vector in the format \"left, top, width, height\" in the space of the base layer. Default value of \"-1, -1, -1, -1\" indicates that the whole image should be processed. as JSON (region)"
},
{
"name": "analysis_tile_size",
"value": "",
"type": "query",
"description": "Tile size for blockwise analysis"
},
{
"name": "foreground_threshold",
"value": "",
"type": "query",
"description": "Intensity value to use as threshold to segment foreground in nuclear stain image"
},
{
"name": "frame",
"value": "",
"type": "query",
"description": "Frame index in a multi-frame image"
},
{
"name": "ignore_border_nuclei",
"value": "",
"type": "query",
"description": "Ignore/drop nuclei touching the image/tile border"
},
{
"name": "ImageInversionForm",
"value": "",
"type": "query",
"description": "Image inversion may be needed for greyscale images with bright nuclei and dark background. default option will automatically invert the image if it is single channel. Choose if color inversion is needed."
},
{
"name": "local_max_search_radius",
"value": "",
"type": "query",
"description": "Local max search radius used for detection seed points in nuclei"
},
{
"name": "max_radius",
"value": "",
"type": "query",
"description": "Maximum nuclear radius (used to set max sigma of the multiscale LoG filter)"
},
{
"name": "min_fgnd_frac",
"value": "",
"type": "query",
"description": "The minimum amount of foreground that must be present in a tile for it to be analyzed"
},
{
"name": "min_nucleus_area",
"value": "",
"type": "query",
"description": "Minimum area that each nucleus should have"
},
{
"name": "min_radius",
"value": "",
"type": "query",
"description": "Minimum nuclear radius (used to set min sigma of the multiscale LoG filter)"
},
{
"name": "nuclei_annotation_format",
"value": "",
"type": "query",
"description": "Format of the output nuclei annotations"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "reference_mu_lab",
"value": "",
"type": "query",
"description": "Mean of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "reference_std_lab",
"value": "",
"type": "query",
"description": "Standard deviation of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "remove_overlapping_nuclei_segmentation",
"value": "",
"type": "query",
"description": "Remove overlapping nuclei segmentation from the given region. It is recommended to use this approach when defining the tile overlap parameter."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
},
{
"name": "style",
"value": "",
"type": "query",
"description": "Image style options for compositing a multi-frame image"
},
{
"name": "tile_overlap_value",
"value": "",
"type": "query",
"description": "Tile overlap size in pixels, Default value of -1 indicate that the tile overlap will be set to (max_radius + 1) * 4"
}
]
},
"docs": "Rerun a previous job: Description:
Detects nuclei in a whole-slide image
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Detects Nuclei",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/NucleiDetection/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image"
},
{
"name": "outputNucleiAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "outputNucleiAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputNucleiAnnotationFile: Output nuclei annotation file (*.anot)"
},
{
"name": "analysis_mag",
"value": "",
"type": "query",
"description": "The magnification at which the analysis should be performed."
},
{
"name": "analysis_roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be done. Must be a four element vector in the format \"left, top, width, height\" in the space of the base layer. Default value of \"-1, -1, -1, -1\" indicates that the whole image should be processed. as JSON (region)"
},
{
"name": "analysis_tile_size",
"value": "",
"type": "query",
"description": "Tile size for blockwise analysis"
},
{
"name": "foreground_threshold",
"value": "",
"type": "query",
"description": "Intensity value to use as threshold to segment foreground in nuclear stain image"
},
{
"name": "frame",
"value": "",
"type": "query",
"description": "Frame index in a multi-frame image"
},
{
"name": "ignore_border_nuclei",
"value": "",
"type": "query",
"description": "Ignore/drop nuclei touching the image/tile border"
},
{
"name": "ImageInversionForm",
"value": "",
"type": "query",
"description": "Image inversion may be needed for greyscale images with bright nuclei and dark background. default option will automatically invert the image if it is single channel. Choose if color inversion is needed."
},
{
"name": "local_max_search_radius",
"value": "",
"type": "query",
"description": "Local max search radius used for detection seed points in nuclei"
},
{
"name": "max_radius",
"value": "",
"type": "query",
"description": "Maximum nuclear radius (used to set max sigma of the multiscale LoG filter)"
},
{
"name": "min_fgnd_frac",
"value": "",
"type": "query",
"description": "The minimum amount of foreground that must be present in a tile for it to be analyzed"
},
{
"name": "min_nucleus_area",
"value": "",
"type": "query",
"description": "Minimum area that each nucleus should have"
},
{
"name": "min_radius",
"value": "",
"type": "query",
"description": "Minimum nuclear radius (used to set min sigma of the multiscale LoG filter)"
},
{
"name": "nuclei_annotation_format",
"value": "",
"type": "query",
"description": "Format of the output nuclei annotations"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "reference_mu_lab",
"value": "",
"type": "query",
"description": "Mean of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "reference_std_lab",
"value": "",
"type": "query",
"description": "Standard deviation of reference image in LAB color space for Reinhard color normalization as JSON (double-vector)"
},
{
"name": "remove_overlapping_nuclei_segmentation",
"value": "",
"type": "query",
"description": "Remove overlapping nuclei segmentation from the given region. It is recommended to use this approach when defining the tile overlap parameter."
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "stain_1",
"value": "",
"type": "query",
"description": "Name of stain-1"
},
{
"name": "stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-1 as JSON (double-vector)"
},
{
"name": "stain_2",
"value": "",
"type": "query",
"description": "Name of stain-2"
},
{
"name": "stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-2 as JSON (double-vector)"
},
{
"name": "stain_3",
"value": "",
"type": "query",
"description": "Name of stain-3"
},
{
"name": "stain_3_vector",
"value": "",
"type": "query",
"description": "Custom value for stain-3 as JSON (double-vector)"
},
{
"name": "style",
"value": "",
"type": "query",
"description": "Image style options for compositing a multi-frame image"
},
{
"name": "tile_overlap_value",
"value": "",
"type": "query",
"description": "Tile overlap size in pixels, Default value of -1 indicate that the tile overlap will be set to (max_radius + 1) * 4"
}
]
},
"docs": "Description:
Detects nuclei in a whole-slide image
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Positive Pixel Count",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/PositivePixelCount/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image in which to count and classify positive pixels"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image in which to count and classify positive pixels"
},
{
"name": "hue_value",
"value": "",
"type": "query",
"description": "Center of the hue range in HSI space for the positive color, in the range [0, 1]"
},
{
"name": "hue_width",
"value": "",
"type": "query",
"description": "Width of the hue range in HSI space"
},
{
"name": "saturation_minimum",
"value": "",
"type": "query",
"description": "Minimum saturation of positive pixels in HSI space, in the range [0, 1]"
},
{
"name": "intensity_upper_limit",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space above which a pixel is considered negative, in the range [0, 1]"
},
{
"name": "intensity_weak_threshold",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space that separates weak-positive pixels (above) from plain positive pixels (below)"
},
{
"name": "intensity_strong_threshold",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space that separates plain positive pixels (above) from strong positive pixels (below)"
},
{
"name": "intensity_lower_limit",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space below which a pixel is considered negative"
},
{
"name": "frame",
"value": "",
"type": "query",
"description": "Frame index in a multi-frame image"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to relate the image to the source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to relate the image to the source (*.anot)"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "outputLabelImage_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputLabelImage: Color-coded image of the region, showing the various classes of pixel"
},
{
"name": "outputLabelImage",
"value": "",
"type": "query",
"description": "Name of output image - outputLabelImage: Color-coded image of the region, showing the various classes of pixel"
},
{
"name": "outputImageForm",
"value": "",
"type": "query",
"description": "The output image can either be colored for easy visibility or coded as categorical values where 0 is negative, 1 weak, 2 plain, and 3 strong"
},
{
"name": "region",
"value": "",
"type": "query",
"description": "Region of interest where analysis is performed. This is either -1,-1,-1,-1 for the whole image, or a four-element vector in the format \"left, top, width, height\", or a list of four or more x,y vertices to specify a polygon. as JSON (region)"
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "style",
"value": "",
"type": "query",
"description": "Image style options for compositing a multi-frame image"
}
]
},
"docs": "Rerun a previous job: Description:
Counts different types of positive pixels based on values in the HSI color space
Version: 0.1.0
License: Apache 2.0
Author(s): David Manthey (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Positive Pixel Count",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/PositivePixelCount/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image in which to count and classify positive pixels"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image in which to count and classify positive pixels"
},
{
"name": "hue_value",
"value": "",
"type": "query",
"description": "Center of the hue range in HSI space for the positive color, in the range [0, 1]"
},
{
"name": "hue_width",
"value": "",
"type": "query",
"description": "Width of the hue range in HSI space"
},
{
"name": "saturation_minimum",
"value": "",
"type": "query",
"description": "Minimum saturation of positive pixels in HSI space, in the range [0, 1]"
},
{
"name": "intensity_upper_limit",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space above which a pixel is considered negative, in the range [0, 1]"
},
{
"name": "intensity_weak_threshold",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space that separates weak-positive pixels (above) from plain positive pixels (below)"
},
{
"name": "intensity_strong_threshold",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space that separates plain positive pixels (above) from strong positive pixels (below)"
},
{
"name": "intensity_lower_limit",
"value": "",
"type": "query",
"description": "Intensity threshold in HSI space below which a pixel is considered negative"
},
{
"name": "frame",
"value": "",
"type": "query",
"description": "Frame index in a multi-frame image"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to relate the image to the source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to relate the image to the source (*.anot)"
},
{
"name": "num_threads_per_worker",
"value": "",
"type": "query",
"description": "Number of threads to use per worker while setting up a local cluster internally. Must be a positive integer >= 1."
},
{
"name": "num_workers",
"value": "",
"type": "query",
"description": "Number of dask workers to start while setting up a local cluster internally. If a negative value is specified then the number of workers is set to number of cpu cores on the machine minus the number of workers specified."
},
{
"name": "outputLabelImage_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputLabelImage: Color-coded image of the region, showing the various classes of pixel"
},
{
"name": "outputLabelImage",
"value": "",
"type": "query",
"description": "Name of output image - outputLabelImage: Color-coded image of the region, showing the various classes of pixel"
},
{
"name": "outputImageForm",
"value": "",
"type": "query",
"description": "The output image can either be colored for easy visibility or coded as categorical values where 0 is negative, 1 weak, 2 plain, and 3 strong"
},
{
"name": "region",
"value": "",
"type": "query",
"description": "Region of interest where analysis is performed. This is either -1,-1,-1,-1 for the whole image, or a four-element vector in the format \"left, top, width, height\", or a list of four or more x,y vertices to specify a polygon. as JSON (region)"
},
{
"name": "scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "style",
"value": "",
"type": "query",
"description": "Image style options for compositing a multi-frame image"
}
]
},
"docs": "Description:
Counts different types of positive pixels based on values in the HSI color space
Version: 0.1.0
License: Apache 2.0
Author(s): David Manthey (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Separate Stains (PCA-based Macenko method)",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/SeparateStainsMacenkoPCA/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "sample_slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - sample_slide_path: Path to input slide image to be deconvolved"
},
{
"name": "sample_slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - sample_slide_path: Path to input slide image to be deconvolved"
},
{
"name": "macenko_I_0",
"value": "",
"type": "query",
"description": "Background intensity in each channel as JSON (double-vector)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "sample_magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling. The default value indicates native scan magnification."
},
{
"name": "macenko_max_angle_percentile",
"value": "",
"type": "query",
"description": "The larger percentile of one of the vectors to pick from the angle distribution"
},
{
"name": "macenko_min_angle_percentile",
"value": "",
"type": "query",
"description": "The smaller percentile of one of the vectors to pick from the angle distribution"
},
{
"name": "sample_min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to\n be sampled from."
},
{
"name": "macenko_minimum_magnitude",
"value": "",
"type": "query",
"description": "The magnitude below which vectors will be excluded from the computation of the angle distribution"
},
{
"name": "sample_sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "dask_scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "sample_tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "sample_tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Rerun a previous job: Description:
Sample the foreground of a slide to compute the stain vectors using the Macenko method.
Version: 0.1.0
License: Apache 2.0
Author(s): Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Separate Stains (PCA-based Macenko method)",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/SeparateStainsMacenkoPCA/run",
"params": [
{
"name": "sample_slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - sample_slide_path: Path to input slide image to be deconvolved"
},
{
"name": "sample_slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - sample_slide_path: Path to input slide image to be deconvolved"
},
{
"name": "macenko_I_0",
"value": "",
"type": "query",
"description": "Background intensity in each channel as JSON (double-vector)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "sample_magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling. The default value indicates native scan magnification."
},
{
"name": "macenko_max_angle_percentile",
"value": "",
"type": "query",
"description": "The larger percentile of one of the vectors to pick from the angle distribution"
},
{
"name": "macenko_min_angle_percentile",
"value": "",
"type": "query",
"description": "The smaller percentile of one of the vectors to pick from the angle distribution"
},
{
"name": "sample_min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to\n be sampled from."
},
{
"name": "macenko_minimum_magnitude",
"value": "",
"type": "query",
"description": "The magnitude below which vectors will be excluded from the computation of the angle distribution"
},
{
"name": "sample_sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "dask_scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "sample_tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "sample_tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Description:
Sample the foreground of a slide to compute the stain vectors using the Macenko method.
Version: 0.1.0
License: Apache 2.0
Author(s): Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Adaptive Color Deconvolution",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/SeparateStainsXuSnmf/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "sample_slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - sample_slide_path: Input image to be deconvolved"
},
{
"name": "sample_slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - sample_slide_path: Input image to be deconvolved"
},
{
"name": "snmf_I_0",
"value": "",
"type": "query",
"description": "Background intensity in each channel as JSON (double-vector)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "snmf_beta",
"value": "",
"type": "query",
"description": "A parameter to control sparsity of stain concentrations"
},
{
"name": "sample_magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling. The default value indicates native scan magnification."
},
{
"name": "sample_min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to\n be sampled from."
},
{
"name": "sample_sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "dask_scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "sample_tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "stains_stain_1",
"value": "",
"type": "query",
"description": "Name for initial estimate of color of stain-1"
},
{
"name": "stains_stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for initial estimate of stain-1 as JSON (double-vector)"
},
{
"name": "stains_stain_2",
"value": "",
"type": "query",
"description": "Name for initial estimate of color of stain-2"
},
{
"name": "stains_stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for initial estimate of stain-2 as JSON (double-vector)"
},
{
"name": "sample_tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Rerun a previous job: Description:
Use sparse non-negative matrix factorization to adaptively deconvolve a given RGB image into intensity images representing distinct stains.
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Adaptive Color Deconvolution",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/SeparateStainsXuSnmf/run",
"params": [
{
"name": "sample_slide_path",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - sample_slide_path: Input image to be deconvolved"
},
{
"name": "sample_slide_path_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - sample_slide_path: Input image to be deconvolved"
},
{
"name": "snmf_I_0",
"value": "",
"type": "query",
"description": "Background intensity in each channel as JSON (double-vector)"
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Output stain annotation file (*.anot)"
},
{
"name": "snmf_beta",
"value": "",
"type": "query",
"description": "A parameter to control sparsity of stain concentrations"
},
{
"name": "sample_magnification",
"value": "",
"type": "query",
"description": "Desired magnification for sampling. The default value indicates native scan magnification."
},
{
"name": "sample_min_coverage",
"value": "",
"type": "query",
"description": "Minimum background coverage required for a tile to\n be sampled from."
},
{
"name": "sample_sample_approximate_total",
"value": "",
"type": "query",
"description": "Use instead of sample_fraction to specify roughly how many pixels to sample. The fewer tiles are excluded, the more accurate this will be."
},
{
"name": "sample_sample_fraction",
"value": "",
"type": "query",
"description": "Fraction of pixels to sample. Specify either this or --sampleApproximateTotal"
},
{
"name": "dask_scheduler",
"value": "",
"type": "query",
"description": "Address of a dask scheduler in the format '127.0.0.1:8786'. Not passing this parameter sets up a dask cluster on the local machine. 'multiprocessing' uses Python multiprocessing. 'multithreading' uses Python multiprocessing in threaded mode."
},
{
"name": "sample_tissue_seg_mag",
"value": "",
"type": "query",
"description": "Low resolution magnification at which foreground and background will be segmented."
},
{
"name": "stains_stain_1",
"value": "",
"type": "query",
"description": "Name for initial estimate of color of stain-1"
},
{
"name": "stains_stain_1_vector",
"value": "",
"type": "query",
"description": "Custom value for initial estimate of stain-1 as JSON (double-vector)"
},
{
"name": "stains_stain_2",
"value": "",
"type": "query",
"description": "Name for initial estimate of color of stain-2"
},
{
"name": "stains_stain_2_vector",
"value": "",
"type": "query",
"description": "Custom value for initial estimate of stain-2 as JSON (double-vector)"
},
{
"name": "sample_tile_grouping",
"value": "",
"type": "query",
"description": "Number of tiles to process as part of a single task"
}
]
},
"docs": "Description:
Use sparse non-negative matrix factorization to adaptively deconvolve a given RGB image into intensity images representing distinct stains.
Version: 0.1.0
License: Apache 2.0
Author(s): Deepak Roy Chittajallu (Kitware), Neal Siekierski (Kitware)
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Superpixel Pixelmap",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/SuperpixelSegmentation/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image for superpixel segmentation"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image for superpixel segmentation"
},
{
"name": "outputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputImageFile: Output Image of Superpixel Pixelmap (*.tiff)"
},
{
"name": "outputImageFile",
"value": "",
"type": "query",
"description": "Name of output image - outputImageFile: Output Image of Superpixel Pixelmap (*.tiff)"
},
{
"name": "boundaries",
"value": "",
"type": "query",
"description": "Mark the boundary around each superpixel. Boundaries are specified with a separate pixelmap index value that is always 1 higher than the pixelmap index value of the superpixel's interior."
},
{
"name": "bounding",
"value": "",
"type": "query",
"description": "If specified, output an annotation with the bounding box of each superpixel. Internal adds a user.bbox field as a single array to the superpixel annotation with the base image coordinates left,top,right,bottom for each superpixel."
},
{
"name": "compactness",
"value": "",
"type": "query",
"description": "Balances color proximity and space proximity. Higher values give more weight to space proximity, making superpixel shapes more square/cubic."
},
{
"name": "default_category_label",
"value": "",
"type": "query",
"description": "Default category label used for superpixels"
},
{
"name": "default_fillColor",
"value": "",
"type": "query",
"description": "Default color for superpixels"
},
{
"name": "default_strokeColor",
"value": "",
"type": "query",
"description": "If creating boundary superpixels, this is the default color of the boundaries of the superpixels"
},
{
"name": "magnification",
"value": "",
"type": "query",
"description": "If specified, the magnification that should be used for the superpixels. If 0, the base magnfication is used"
},
{
"name": "overlap",
"value": "",
"type": "query",
"description": "If specified, overlap tile computation to avoid edge effects."
},
{
"name": "roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be run as JSON (region)"
},
{
"name": "sigma",
"value": "",
"type": "query",
"description": "Width of Gaussian smoothing kernel for pre-processing for each dimension of the image. The same sigma is applied to each dimension in case of a scalar value. Zero means no smoothing."
},
{
"name": "slic_zero",
"value": "",
"type": "query",
"description": "If true, run the algorithm in SLIC0 mode to adaptively determine compactness for each superpixel."
},
{
"name": "superpixelSize",
"value": "",
"type": "query",
"description": "Approximate diameter of the average superpixel."
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to display pixelmap on source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to display pixelmap on source (*.anot)"
},
{
"name": "tileSize",
"value": "",
"type": "query",
"description": "Specify the size of the working tile. If there is no overlap, superpixel boundaries will appear at these locations."
}
]
},
"docs": "Rerun a previous job: Description:
Create a pixelmap image of superpixels using SLIC.
Version: 0.1.0
License: Apache 2.0
Author(s): Kitware
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Superpixel Pixelmap",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/dsarchive_histomicstk_latest/SuperpixelSegmentation/run",
"params": [
{
"name": "inputImageFile",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - inputImageFile: Input image for superpixel segmentation"
},
{
"name": "inputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - inputImageFile: Input image for superpixel segmentation"
},
{
"name": "outputImageFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - outputImageFile: Output Image of Superpixel Pixelmap (*.tiff)"
},
{
"name": "outputImageFile",
"value": "",
"type": "query",
"description": "Name of output image - outputImageFile: Output Image of Superpixel Pixelmap (*.tiff)"
},
{
"name": "boundaries",
"value": "",
"type": "query",
"description": "Mark the boundary around each superpixel. Boundaries are specified with a separate pixelmap index value that is always 1 higher than the pixelmap index value of the superpixel's interior."
},
{
"name": "bounding",
"value": "",
"type": "query",
"description": "If specified, output an annotation with the bounding box of each superpixel. Internal adds a user.bbox field as a single array to the superpixel annotation with the base image coordinates left,top,right,bottom for each superpixel."
},
{
"name": "compactness",
"value": "",
"type": "query",
"description": "Balances color proximity and space proximity. Higher values give more weight to space proximity, making superpixel shapes more square/cubic."
},
{
"name": "default_category_label",
"value": "",
"type": "query",
"description": "Default category label used for superpixels"
},
{
"name": "default_fillColor",
"value": "",
"type": "query",
"description": "Default color for superpixels"
},
{
"name": "default_strokeColor",
"value": "",
"type": "query",
"description": "If creating boundary superpixels, this is the default color of the boundaries of the superpixels"
},
{
"name": "magnification",
"value": "",
"type": "query",
"description": "If specified, the magnification that should be used for the superpixels. If 0, the base magnfication is used"
},
{
"name": "overlap",
"value": "",
"type": "query",
"description": "If specified, overlap tile computation to avoid edge effects."
},
{
"name": "roi",
"value": "",
"type": "query",
"description": "Region of interest within which the analysis should be run as JSON (region)"
},
{
"name": "sigma",
"value": "",
"type": "query",
"description": "Width of Gaussian smoothing kernel for pre-processing for each dimension of the image. The same sigma is applied to each dimension in case of a scalar value. Zero means no smoothing."
},
{
"name": "slic_zero",
"value": "",
"type": "query",
"description": "If true, run the algorithm in SLIC0 mode to adaptively determine compactness for each superpixel."
},
{
"name": "superpixelSize",
"value": "",
"type": "query",
"description": "Approximate diameter of the average superpixel."
},
{
"name": "outputAnnotationFile_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output file - outputAnnotationFile: Annotation to display pixelmap on source (*.anot)"
},
{
"name": "outputAnnotationFile",
"value": "",
"type": "query",
"description": "Name of output file - outputAnnotationFile: Annotation to display pixelmap on source (*.anot)"
},
{
"name": "tileSize",
"value": "",
"type": "query",
"description": "Specify the size of the working tile. If there is no overlap, superpixel boundaries will appear at these locations."
}
]
},
"docs": "Description:
Create a pixelmap image of superpixels using SLIC.
Version: 0.1.0
License: Apache 2.0
Author(s): Kitware
Acknowledgements: This work is part of the HistomicsTK project."
},
{
"info": {
"name": "Rerun Simple Get Region",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/jvizcar_braak-study_cli-tasks/hp_tau_detection/rerun",
"params": [
{
"name": "jobId",
"value": "",
"type": "query",
"description": "The previous job ID"
},
{
"name": "in_file",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - in_file: Input image"
},
{
"name": "in_file_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - in_file: Input image"
},
{
"name": "mag",
"value": "",
"type": "query",
"description": "Output thumbnail magnification"
},
{
"name": "out_file_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - out_file: Output Region Image file"
},
{
"name": "out_file",
"value": "",
"type": "query",
"description": "Name of output image - out_file: Output Region Image file"
},
{
"name": "girderApiUrl",
"value": "",
"type": "query",
"description": "A Girder API URL (e.g., https://girder.example.com:443/api/v1)"
},
{
"name": "girderToken",
"value": "",
"type": "query",
"description": "A Girder token"
}
]
},
"docs": "Rerun a previous job: Description:
Simple Get Region
Version: 0.1.0
License: Apache 2.0
Author(s): David Gutman and Jc Vizcarra"
},
{
"info": {
"name": "Simple Get Region",
"type": "http"
},
"http": {
"method": "POST",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/jvizcar_braak-study_cli-tasks/hp_tau_detection/run",
"params": [
{
"name": "in_file",
"value": "",
"type": "query",
"description": "Girder ID of input image (if batch input, this is a regex for item names) - in_file: Input image"
},
{
"name": "in_file_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for batch input image - in_file: Input image"
},
{
"name": "mag",
"value": "",
"type": "query",
"description": "Output thumbnail magnification"
},
{
"name": "out_file_folder",
"value": "",
"type": "query",
"description": "Girder ID of parent folder for output image - out_file: Output Region Image file"
},
{
"name": "out_file",
"value": "",
"type": "query",
"description": "Name of output image - out_file: Output Region Image file"
},
{
"name": "girderApiUrl",
"value": "",
"type": "query",
"description": "A Girder API URL (e.g., https://girder.example.com:443/api/v1)"
},
{
"name": "girderToken",
"value": "",
"type": "query",
"description": "A Girder token"
}
]
},
"docs": "Description:
Simple Get Region
Version: 0.1.0
License: Apache 2.0
Author(s): David Gutman and Jc Vizcarra"
},
{
"info": {
"name": "Get the most recently updated resource that has a name and path that matches a regular expression",
"type": "http"
},
"http": {
"method": "GET",
"url": "https://computablebrain.emory.edu/api/v1/slicer_cli_web/path_match",
"params": [
{
"name": "name",
"value": "",
"type": "query",
"description": "A regular expression to match the name of the resource."
},
{
"name": "path",
"value": "",
"type": "query",
"description": "A regular expression to match the entire resource path."
},
{
"name": "relative_path",
"value": "",
"type": "query",
"description": "A relative resource path to the base item."
},
{
"name": "base_id",
"value": "",
"type": "query",
"description": "The base girder id for the relative path"
},
{
"name": "base_type",
"value": "",
"type": "query",
"description": "The base girder type for the relative path"
},
{
"name": "type",
"value": "",
"type": "query",
"description": "The type of the resource (item, file, etc.)."
}
]
},
"docs": "This can be very slow if name is too general."
}
]
}
],
"bundled": true
}