|
| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "code", |
| 5 | + "execution_count": 1, |
| 6 | + "id": "196c6071", |
| 7 | + "metadata": {}, |
| 8 | + "outputs": [], |
| 9 | + "source": [ |
| 10 | + "import sys\n", |
| 11 | + "\n", |
| 12 | + "import itk\n", |
| 13 | + "\n", |
| 14 | + "from itkwidgets import view" |
| 15 | + ] |
| 16 | + }, |
| 17 | + { |
| 18 | + "cell_type": "code", |
| 19 | + "execution_count": 2, |
| 20 | + "id": "52104b31", |
| 21 | + "metadata": {}, |
| 22 | + "outputs": [ |
| 23 | + { |
| 24 | + "data": { |
| 25 | + "application/vnd.jupyter.widget-view+json": { |
| 26 | + "model_id": "f93f02adae4d47c7add2409a5f97b075", |
| 27 | + "version_major": 2, |
| 28 | + "version_minor": 0 |
| 29 | + }, |
| 30 | + "text/plain": [ |
| 31 | + "Viewer(geometries=[], gradient_opacity=0.22, point_sets=[], rendered_image=<itk.itkImagePython.itkImageF2; pro…" |
| 32 | + ] |
| 33 | + }, |
| 34 | + "metadata": {}, |
| 35 | + "output_type": "display_data" |
| 36 | + } |
| 37 | + ], |
| 38 | + "source": [ |
| 39 | + "InputPixelType = itk.ctype('float')\n", |
| 40 | + "\n", |
| 41 | + "input_image = itk.imread('./BrainProtonDensitySlice.png', InputPixelType)\n", |
| 42 | + "\n", |
| 43 | + "view(input_image)" |
| 44 | + ] |
| 45 | + }, |
| 46 | + { |
| 47 | + "cell_type": "code", |
| 48 | + "execution_count": 3, |
| 49 | + "id": "4297e2ac", |
| 50 | + "metadata": {}, |
| 51 | + "outputs": [ |
| 52 | + { |
| 53 | + "data": { |
| 54 | + "application/vnd.jupyter.widget-view+json": { |
| 55 | + "model_id": "ec1c09bacc97419f8da1825563aa36bc", |
| 56 | + "version_major": 2, |
| 57 | + "version_minor": 0 |
| 58 | + }, |
| 59 | + "text/plain": [ |
| 60 | + "Viewer(geometries=[], gradient_opacity=0.22, point_sets=[], rendered_image=<itk.itkImagePython.itkImageF2; pro…" |
| 61 | + ] |
| 62 | + }, |
| 63 | + "metadata": {}, |
| 64 | + "output_type": "display_data" |
| 65 | + } |
| 66 | + ], |
| 67 | + "source": [ |
| 68 | + "smoothed = itk.curvature_anisotropic_diffusion_image_filter(input_image,\n", |
| 69 | + " time_step=0.125,\n", |
| 70 | + " number_of_iterations=5,\n", |
| 71 | + " conductance_parameter=9.0)\n", |
| 72 | + "view(smoothed)" |
| 73 | + ] |
| 74 | + }, |
| 75 | + { |
| 76 | + "cell_type": "code", |
| 77 | + "execution_count": 4, |
| 78 | + "id": "99186583", |
| 79 | + "metadata": {}, |
| 80 | + "outputs": [ |
| 81 | + { |
| 82 | + "data": { |
| 83 | + "application/vnd.jupyter.widget-view+json": { |
| 84 | + "model_id": "dd0a1ba394ed4cab87b0c79e7b9a137d", |
| 85 | + "version_major": 2, |
| 86 | + "version_minor": 0 |
| 87 | + }, |
| 88 | + "text/plain": [ |
| 89 | + "Viewer(geometries=[], gradient_opacity=0.22, point_sets=[], rendered_image=<itk.itkImagePython.itkImageF2; pro…" |
| 90 | + ] |
| 91 | + }, |
| 92 | + "metadata": {}, |
| 93 | + "output_type": "display_data" |
| 94 | + } |
| 95 | + ], |
| 96 | + "source": [ |
| 97 | + "sigma = 1.0\n", |
| 98 | + "\n", |
| 99 | + "gradient_magnitude = itk.gradient_magnitude_recursive_gaussian_image_filter(smoothed,\n", |
| 100 | + " sigma=sigma)\n", |
| 101 | + "view(gradient_magnitude)" |
| 102 | + ] |
| 103 | + }, |
| 104 | + { |
| 105 | + "cell_type": "code", |
| 106 | + "execution_count": 5, |
| 107 | + "id": "8a219f34", |
| 108 | + "metadata": {}, |
| 109 | + "outputs": [ |
| 110 | + { |
| 111 | + "data": { |
| 112 | + "application/vnd.jupyter.widget-view+json": { |
| 113 | + "model_id": "4839685882a04ed3a697f3e947458368", |
| 114 | + "version_major": 2, |
| 115 | + "version_minor": 0 |
| 116 | + }, |
| 117 | + "text/plain": [ |
| 118 | + "Viewer(geometries=[], gradient_opacity=0.22, point_sets=[], rendered_image=<itk.itkImagePython.itkImageF2; pro…" |
| 119 | + ] |
| 120 | + }, |
| 121 | + "metadata": {}, |
| 122 | + "output_type": "display_data" |
| 123 | + } |
| 124 | + ], |
| 125 | + "source": [ |
| 126 | + "alpha = -0.5\n", |
| 127 | + "beta = 3.0\n", |
| 128 | + "\n", |
| 129 | + "sigmoid = itk.sigmoid_image_filter(gradient_magnitude,\n", |
| 130 | + " output_minimum=0.0,\n", |
| 131 | + " output_maximum=1.0,\n", |
| 132 | + " alpha=alpha,\n", |
| 133 | + " beta=beta)\n", |
| 134 | + "\n", |
| 135 | + "view(sigmoid)" |
| 136 | + ] |
| 137 | + }, |
| 138 | + { |
| 139 | + "cell_type": "code", |
| 140 | + "execution_count": 6, |
| 141 | + "id": "499443a8", |
| 142 | + "metadata": {}, |
| 143 | + "outputs": [], |
| 144 | + "source": [ |
| 145 | + "Dimension = input_image.GetImageDimension()\n", |
| 146 | + "seeds = itk.VectorContainer[itk.UI, itk.LevelSetNode[InputPixelType, Dimension]].New()\n", |
| 147 | + "seeds.Initialize()\n", |
| 148 | + "\n", |
| 149 | + "seed_position = itk.Index[Dimension]()\n", |
| 150 | + "seed_position[0] = 81\n", |
| 151 | + "seed_position[1] = 114\n", |
| 152 | + "node = itk.LevelSetNode[InputPixelType, Dimension]()\n", |
| 153 | + "node.SetValue(-5.0)\n", |
| 154 | + "node.SetIndex(seed_position)\n", |
| 155 | + "seeds.InsertElement(0, node)\n", |
| 156 | + "\n", |
| 157 | + "fast_marching = itk.fast_marching_image_filter(trial_points=seeds,\n", |
| 158 | + " speed_constant=1.0,\n", |
| 159 | + " output_size=input_image.GetBufferedRegion().GetSize())" |
| 160 | + ] |
| 161 | + }, |
| 162 | + { |
| 163 | + "cell_type": "code", |
| 164 | + "execution_count": 7, |
| 165 | + "id": "d2c5e205", |
| 166 | + "metadata": {}, |
| 167 | + "outputs": [ |
| 168 | + { |
| 169 | + "data": { |
| 170 | + "application/vnd.jupyter.widget-view+json": { |
| 171 | + "model_id": "8d762859e81a48698841081217638423", |
| 172 | + "version_major": 2, |
| 173 | + "version_minor": 0 |
| 174 | + }, |
| 175 | + "text/plain": [ |
| 176 | + "Viewer(geometries=[], gradient_opacity=0.22, point_sets=[], rendered_image=<itk.itkImagePython.itkImageF2; pro…" |
| 177 | + ] |
| 178 | + }, |
| 179 | + "metadata": {}, |
| 180 | + "output_type": "display_data" |
| 181 | + } |
| 182 | + ], |
| 183 | + "source": [ |
| 184 | + "propagation_scaling = 2.0\n", |
| 185 | + "number_of_iterations = 800\n", |
| 186 | + "\n", |
| 187 | + "geodesic_active_contour = \\\n", |
| 188 | + " itk.geodesic_active_contour_level_set_image_filter(fast_marching,\n", |
| 189 | + " propagation_scaling=propagation_scaling,\n", |
| 190 | + " curvature_scaling=1.0,\n", |
| 191 | + " advection_scaling=1.0,\n", |
| 192 | + " maximum_r_m_s_error=0.02,\n", |
| 193 | + " number_of_iterations=number_of_iterations,\n", |
| 194 | + " feature_image=sigmoid)\n", |
| 195 | + "\n", |
| 196 | + "view(geodesic_active_contour)" |
| 197 | + ] |
| 198 | + }, |
| 199 | + { |
| 200 | + "cell_type": "code", |
| 201 | + "execution_count": 8, |
| 202 | + "id": "1269f1b4", |
| 203 | + "metadata": {}, |
| 204 | + "outputs": [], |
| 205 | + "source": [ |
| 206 | + "OutputPixelType = itk.ctype('unsigned char')\n", |
| 207 | + "thresholded = itk.binary_threshold_image_filter(geodesic_active_contour,\n", |
| 208 | + " lower_threshold=-1000.0,\n", |
| 209 | + " upper_threshold=0.0,\n", |
| 210 | + " outside_value=itk.NumericTraits[OutputPixelType].min(),\n", |
| 211 | + " inside_value=itk.NumericTraits[OutputPixelType].max(),\n", |
| 212 | + " ttype=[type(geodesic_active_contour), itk.Image[OutputPixelType,Dimension]])" |
| 213 | + ] |
| 214 | + }, |
| 215 | + { |
| 216 | + "cell_type": "code", |
| 217 | + "execution_count": 9, |
| 218 | + "id": "58bdf582", |
| 219 | + "metadata": {}, |
| 220 | + "outputs": [ |
| 221 | + { |
| 222 | + "data": { |
| 223 | + "application/vnd.jupyter.widget-view+json": { |
| 224 | + "model_id": "9c693a5687134f269fd009babaae2e29", |
| 225 | + "version_major": 2, |
| 226 | + "version_minor": 0 |
| 227 | + }, |
| 228 | + "text/plain": [ |
| 229 | + "Viewer(geometries=[], gradient_opacity=0.22, point_sets=[], rendered_image=<itk.itkImagePython.itkImageUC2; pr…" |
| 230 | + ] |
| 231 | + }, |
| 232 | + "metadata": {}, |
| 233 | + "output_type": "display_data" |
| 234 | + } |
| 235 | + ], |
| 236 | + "source": [ |
| 237 | + "view(thresholded)" |
| 238 | + ] |
| 239 | + } |
| 240 | + ], |
| 241 | + "metadata": { |
| 242 | + "kernelspec": { |
| 243 | + "display_name": "Python 3", |
| 244 | + "language": "python", |
| 245 | + "name": "python3" |
| 246 | + }, |
| 247 | + "language_info": { |
| 248 | + "codemirror_mode": { |
| 249 | + "name": "ipython", |
| 250 | + "version": 3 |
| 251 | + }, |
| 252 | + "file_extension": ".py", |
| 253 | + "mimetype": "text/x-python", |
| 254 | + "name": "python", |
| 255 | + "nbconvert_exporter": "python", |
| 256 | + "pygments_lexer": "ipython3", |
| 257 | + "version": "3.8.6" |
| 258 | + } |
| 259 | + }, |
| 260 | + "nbformat": 4, |
| 261 | + "nbformat_minor": 5 |
| 262 | +} |
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