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airways_data.dtype)\n", "\n", "lungs_image = nib.load(patient_1[\"lungs\"])\n", "lungs_image = resample_to_output(lungs_image, order=0)\n", "lungs_data = lungs_image.get_fdata().astype(\"uint8\")\n", "\n", "print(\"Lungs:\", lungs_data.shape, lungs_data.dtype)\n", "\n", "# HU-clip CT for better contrast\n", "ct_data[ct_data < -1024] = -1024\n", "ct_data[ct_data > 400] = 400\n", "\n", "# plot corresponding CT, Airways, and Lungs for a single 2D slide side-by-side\n", "fig, ax = plt.subplots(1, 3, figsize=(20, 12))\n", "ax[0].imshow(ct_data[..., slice_nr], cmap=\"gray\")\n", "ax[1].imshow(airways_data[..., slice_nr], cmap=\"gray\")\n", "ax[2].imshow(lungs_data[..., slice_nr], cmap=\"gray\")\n", "\n", "for i, title in enumerate([\"CT\", \"Airways\", \"Lungs\"]):\n", " ax[i].set_title(title)\n", "plt.show()" ] } ], "metadata": { "colab": { "authorship_tag": "ABX9TyO+FqbZLfyG+4ejr+fhLd0A", "include_colab_link": true, "provenance": [], "toc_visible": true }, "kernelspec": { "display_name": 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