{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define Content of Interest with Image Masks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Often, some content in the images may not correspond. For example, there may be background content or noisy areas. A mask defined on the fixed and/or moving image can be used to exclude these regions at a pixel level from the similarity metric computations. This improves the robustness of registration.\n",
    "\n",
    "For more information, see Section 5.4, \"Masks\" of the [Elastix Manual](http://elastix.isi.uu.nl/download/elastix-5.0.0-manual.pdf)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import itk\n",
    "from itkwidgets import view, compare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Lung SEM slices\n",
    "# Grothausmann, R., Knudsen, L., Ochs, M., and Mühlfeld, C.: Digital 3D reconstructions\n",
    "# using histological serial sections of lung tissue including the alveolar\n",
    "# capillary network. American Journal of Physiology - Lung Cellular and Molecular\n",
    "# Physiology 312(2), L243–L257 (2017). doi: 10.1152/ajplung.00326.2016\n",
    "fixed = itk.imread('data/lung_sem/2016_12_02_0101_s00_01.png', itk.F)\n",
    "moving = itk.imread('data/lung_sem/2016_12_02_0101_s00_02.png', itk.F)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are inconsistent dirt particles in each slice. Let's exclude these with a mask."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6a9cf64c1f8442ab938853ea5c0f0f70",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "AppLayout(children=(HBox(children=(Label(value='Link:'), Checkbox(value=False, description='cmap'), Checkbox(v…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare(fixed, moving, ui_collapsed=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3945015b073c4681a5ca64160bb79c4a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "AppLayout(children=(HBox(children=(Label(value='Link:'), Checkbox(value=False, description='cmap'), Checkbox(v…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MaskImageType = itk.Image[itk.UC, 2]\n",
    "fixed_mask = itk.binary_threshold_image_filter(fixed,\n",
    "                                               lower_threshold=80.0,\n",
    "                                               inside_value=1,\n",
    "                                               ttype=(type(fixed), MaskImageType))\n",
    "compare(fixed, fixed_mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c79ea51ca8854d44827a01af9f111a30",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "AppLayout(children=(HBox(children=(Label(value='Link:'), Checkbox(value=False, description='cmap'), Checkbox(v…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "moving_mask = itk.binary_threshold_image_filter(moving,\n",
    "                                                lower_threshold=80.0,\n",
    "                                                inside_value=1,\n",
    "                                                ttype=(type(moving), MaskImageType))\n",
    "compare(moving, moving_mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "parameters = itk.ParameterObject.New()\n",
    "parameters.ReadParameterFile('data/lung_sem/ParameterFile.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "registered = itk.elastix_registration_method(fixed, moving,\n",
    "                                             parameter_object=parameters,\n",
    "                                             fixed_mask=fixed_mask, moving_mask=moving_mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "99959b78b0a340cd9572c22a5efaff79",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "AppLayout(children=(HBox(children=(Label(value='Link:'), Checkbox(value=False, description='cmap'), Checkbox(v…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare(fixed, registered, ui_collapsed=True)"
   ]
  }
 ],
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