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geodesic notebook #277
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48 changes: 24 additions & 24 deletions
48
src/Segmentation/LevelSets/SegmentWithGeodesicActiveContourLevelSet/CMakeLists.txt
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195 changes: 195 additions & 0 deletions
195
src/Segmentation/LevelSets/SegmentWithGeodesicActiveContourLevelSet/Code.ipynb
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,195 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "7c8b935b", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Segment with geodesic active contour level set" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "196c6071", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import sys\n", | ||
| "import os\n", | ||
| "from urllib.request import urlretrieve\n", | ||
| "\n", | ||
| "import itk\n", | ||
| "\n", | ||
| "from itkwidgets import view" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "d6f35e01", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "input_filename = 'BrainProtonDensitySlice.png'\n", | ||
| "if not os.path.exists(input_filename):\n", | ||
| " url = 'https://data.kitware.com/api/v1/file/57b5d8028d777f10f2694bbf/download'\n", | ||
| " urlretrieve(url, input_filename)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "52104b31", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "InputPixelType = itk.ctype('float')\n", | ||
| "\n", | ||
| "input_image = itk.imread(input_filename, InputPixelType)\n", | ||
| "\n", | ||
| "view(input_image)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "4297e2ac", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "smoothed = itk.curvature_anisotropic_diffusion_image_filter(input_image,\n", | ||
| " time_step=0.125,\n", | ||
| " number_of_iterations=5,\n", | ||
| " conductance_parameter=9.0)\n", | ||
| "view(smoothed)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "99186583", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "sigma = 1.0\n", | ||
| "\n", | ||
| "gradient_magnitude = itk.gradient_magnitude_recursive_gaussian_image_filter(smoothed,\n", | ||
| " sigma=sigma)\n", | ||
| "view(gradient_magnitude)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "8a219f34", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "alpha = -0.5\n", | ||
| "beta = 3.0\n", | ||
| "\n", | ||
| "sigmoid = itk.sigmoid_image_filter(gradient_magnitude,\n", | ||
| " output_minimum=0.0,\n", | ||
| " output_maximum=1.0,\n", | ||
| " alpha=alpha,\n", | ||
| " beta=beta)\n", | ||
| "\n", | ||
| "view(sigmoid)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "499443a8", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "Dimension = input_image.GetImageDimension()\n", | ||
| "seeds = itk.VectorContainer[itk.UI, itk.LevelSetNode[InputPixelType, Dimension]].New()\n", | ||
| "seeds.Initialize()\n", | ||
| "\n", | ||
| "seed_position = itk.Index[Dimension]()\n", | ||
| "seed_position[0] = 81\n", | ||
| "seed_position[1] = 114\n", | ||
| "node = itk.LevelSetNode[InputPixelType, Dimension]()\n", | ||
| "node.SetValue(-5.0)\n", | ||
| "node.SetIndex(seed_position)\n", | ||
| "seeds.InsertElement(0, node)\n", | ||
| "\n", | ||
| "fast_marching = itk.fast_marching_image_filter(trial_points=seeds,\n", | ||
| " speed_constant=1.0,\n", | ||
| " output_size=input_image.GetBufferedRegion().GetSize())" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "d2c5e205", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "propagation_scaling = 2.0\n", | ||
| "number_of_iterations = 800\n", | ||
| "\n", | ||
| "geodesic_active_contour = \\\n", | ||
| " itk.geodesic_active_contour_level_set_image_filter(fast_marching,\n", | ||
| " propagation_scaling=propagation_scaling,\n", | ||
| " curvature_scaling=1.0,\n", | ||
| " advection_scaling=1.0,\n", | ||
| " maximum_r_m_s_error=0.02,\n", | ||
| " number_of_iterations=number_of_iterations,\n", | ||
| " feature_image=sigmoid)\n", | ||
| "\n", | ||
| "view(geodesic_active_contour)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "1269f1b4", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "OutputPixelType = itk.ctype('unsigned char')\n", | ||
| "thresholded = itk.binary_threshold_image_filter(geodesic_active_contour,\n", | ||
| " lower_threshold=-1000.0,\n", | ||
| " upper_threshold=0.0,\n", | ||
| " outside_value=itk.NumericTraits[OutputPixelType].min(),\n", | ||
| " inside_value=itk.NumericTraits[OutputPixelType].max(),\n", | ||
| " ttype=[type(geodesic_active_contour), itk.Image[OutputPixelType,Dimension]])" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "58bdf582", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "view(thresholded)" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.8.6" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } | ||
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Point picker for itkwidgets would come in handy here for interactive experimentation.
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Yes, on the agenda :-).