QuantificationDWModeling0.0.1http://wiki.slicer.org/slicerWiki/index.php/Documentation/Nightly/Modules/DWModelingSlicerAndriy Fedorov (SPL/BWH)This work was partially funded by NIH grants R01 CA160902 (PI Maier) and U24 CA180918 (PIs Kikinis/Fedorov). Input parametersimageNameinputInput DWI MRI trace multivolume image0modelNamemodelSelect the mathematical model used to fit the dataBiExponentialMonoExponentialBiExponentialKurtosisGammaStretchedExponentialmaskNamemaskinputInput mask. Optional; if not specified, fitting will be done at all voxels.bValuesToIncludebvalIncludeList of integers corresponding to the b-values that should be included in fitting data. Note that only one of the two lists (inlusion or exclusion) should be populated, or both can be empty, in which case all b-values will be used. Optional; if not defined, all b-values will be used.bValuesToExcludebvalExcludeList of integers corresponding to the b-values that should be excluded from fitting data. Note that only one of the two lists (inlusion or exclusion) should be populated, or both can be empty, in which case all b-values will be used. Optional; if not defined, all b-values will be used.fittedVolumeFileNamefittedVolumeOutput volume containing the values of the fitted functionoutputrsqrVolumeFileNamersqrVolumeOutput volume containing the R^2 measure of the quality of fit. This measure is calculated only for the b-values used in the fitting process.outputssdFittedVolumeFileNamessdFittedVolumeVolume with the pixel-wise sum of squared differences (SSD) map that takes into consideration only those b-values that were used in the fitting processoutputssdVolumeFileNamessdVolumeVolume with the pixel-wise sum of squared differences (SSD) map that takes into consideration all b-values. Note that this map will be identical to the previous one if the fitting procedure utilized all b-valuesoutputcsFittedVolumeFileNamecsFittedVolumeVolume with the pixel-wise chi squared map that takes into consideration only those b-values that were used in the fitting processoutputcsVolumeFileNamecsVolumeVolume with the pixel-wise pixel-wise chi squared map that takes into consideration all b-values. Note that this map will be identical to the previous one if the fitting procedure utilized all b-valuesoutputadcMapFileNameadcMonoExpDiffoutputDiffusion coefficient map of the mono-exponential modelslowDiffMapFileNameslowDiffoutputSlow diffusion coefficient map of the bi-exponential modelfastDiffMapFileNamefastDiffoutputFast diffusion coefficient map of the bi-exponential modelfastDiffFractionMapFileNamefastDiffFractionoutputFast diffusion fraction map of the bi-exponential modelkurtosisDiffMapFileNamekurtosisDiffoutputDiffusion coefficient map of the kurtosis modelkurtosisMapFileNamekurtosisoutputKurtosos mapSee Oshio et al. 2014thetaMapFileNamethetaoutputTheta parameter of the gamma distribution modelkMapFileNamekoutputk map of the gamma distribution modelmodeMapFileNamemodeoutputMode map of the gamma distribution model ( (k-1)*theta )See Bennett et al. 2003DDCMapFileNameddcoutputDistributed Diffusion Coefficient mapalphaMapFileNamealphaoutputStretching parameter (alpha) mapModel-specific initial parametersmonoExpInitParametersmonoExpInitParametersList of initial model parameters in the following format (all numbers are floating point):initialScale,initialADC0,0.0015biExpInitParametersbiExpInitParametersList of initial model parameters in the following format (all numbers are floating point):initialScale,initialFastDiffusionFraction,initialSlowDiffusionCoefficient,initialFastDiffusionCoefficient0,0.7,0.00025,0.002kurtosisInitParameterskurtosisInitParametersList of initial model parameters in the following format (all numbers are floating point):initialScale,initialKurtosis,initialKurtosisDiffusion0,1,0.0015stretchedExpInitParametersstretchedExpInitParametersList of initial model parameters in the following format (all numbers are floating point):initialScale,initialDDC,initialAlpha0,0.0017,0.7gammaInitParametersgammaInitParametersList of initial model parameters in the following format (all numbers are floating point):initialScale,initialK,initialTheta0,1.5,0.002