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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import voxel as vx\n",
"import tunnelvision as tv\n",
"import numpy as np\n",
"\n",
"mv = vx.load(\"./segmentations/converted_dcm.nii.gz\")\n",
"mv = mv.reformat((\"LR\", \"PA\", \"IS\"))\n",
"np_mv = mv.A\n",
"np_mv = np_mv.astype(np.int32)\n",
"np_mv = np.expand_dims(np_mv, axis=0)\n",
"np_mv = np.expand_dims(np_mv, axis=4)\n",
"\n",
"seg = vx.load(\"./rois/roi.nii.gz\")\n",
"np_seg = seg.A\n",
"np_seg_dim = seg.A\n",
"np_seg = np_seg.astype(np.int32)\n",
"np_seg = np.expand_dims(np_seg, axis=0)\n",
"np_seg = np.expand_dims(np_seg, axis=4)\n",
"\n",
"hip_seg = vx.load(\"./segmentations/hip.nii.gz\")\n",
"hip_seg = hip_seg.reformat((\"LR\", \"PA\", \"IS\"))\n",
"np_hip_seg = hip_seg.A.astype(int)\n",
"# set values not equal to 88 or 89 to 0\n",
"np_hip_seg[(np_hip_seg != 88) & (np_hip_seg != 89)] = 0\n",
"np_hip_seg[np_hip_seg != 0] = np_hip_seg[np_hip_seg != 0] + 4\n",
"np_hip_seg[np_seg_dim != 0] = 0\n",
"np_hip_seg = np_hip_seg.astype(np.int32)\n",
"np_hip_seg = np.expand_dims(np_hip_seg, axis=0)\n",
"np_hip_seg = np.expand_dims(np_hip_seg, axis=4)\n",
"\n",
"ax = tv.Axes(figsize=(512, 512))\n",
"ax.imshow(np_mv)\n",
"ax.imshow(np_seg, cmap=\"seg\")\n",
"ax.imshow(np_hip_seg, cmap=\"seg\")\n",
"ax.show()"
]
}
],
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"display_name": "Python 3.8.16 ('c2c_env')",
"language": "python",
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"file_extension": ".py",
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"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.16"
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"orig_nbformat": 4,
"vscode": {
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}
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