diff --git a/panoptica/example_vertebral.ipynb b/panoptica/example_vertebral.ipynb new file mode 100644 index 0000000..2651e76 --- /dev/null +++ b/panoptica/example_vertebral.ipynb @@ -0,0 +1,579 @@ +{ + "cells": [ + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "# Panoptica Tutorial: Vertebra Metastasis Evaluation\n", + "\n", + "This tutorial shows the concepts for evaluating complex targets like Vertebra lesions using the **Panoptica API**.\n", + "\n", + "You will learn how to:\n", + "1. Define a clear **Taxonomy** (Things, Stuff, Parts) for Vertebra lesion segmentation problem.\n", + "2. Perform **Global Panoptic Quality (PQ)** evaluation, comparing strict 1:1 matching with flexible N:1 matching to handle fragmented predictions.\n", + "3. Incorporate anatomical knowledge for **Region-Wise Evaluation** across the individual vertebrae.\n", + "4. Perform **Threshold Analysis** and calculate the **Area Under Threshold Curve (AUTC)** for a robust, threshold-independent performance metric.\n" + ], + "id": "fc74e62f81225592" + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## 0. Setup & Imports", + "id": "5fde8ea27758b0f2" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-05-06T18:33:41.113739Z", + "start_time": "2026-05-06T18:33:41.107016Z" + } + }, + "cell_type": "code", + "source": "# !pip install panoptica nibabel matplotlib numpy rich scikit-learn > /dev/null", + "id": "1a8f9ecb8b15bdd", + "outputs": [], + "execution_count": 13 + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "import sys\n", + "\n", + "try:\n", + " import google.colab\n", + "\n", + " colabFlag = True\n", + "except ImportError:\n", + " colabFlag = False\n", + "\n", + "if colabFlag:\n", + " from google.colab import drive\n", + "\n", + " drive.mount(\"/content/drive\")\n", + " !git clone https://github.com/BrainLesion/tutorials.git /content/drive/MyDrive/tutorials\n", + " BASE_PATH = \"/content/drive/MyDrive/tutorials/panoptica\"\n", + " sys.path.insert(0, BASE_PATH)\n", + "else:\n", + " BASE_PATH = \".\"" + ], + "id": "df05de2f688f3cd2" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "import os\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import nibabel as nib\n", + "import numpy as np\n", + "from IPython.display import Image, display\n", + "from rich import print as rprint\n", + "from sklearn.metrics import auc\n", + "\n", + "from panoptica import (\n", + " ConnectedComponentsInstanceApproximator,\n", + " InputType,\n", + " Metric,\n", + " Panoptica_Evaluator,\n", + ")\n", + "from panoptica.instance_matcher import (\n", + " MaxBipartiteMatching,\n", + " MaximizeMergeMatching,\n", + " NaiveThresholdMatching,\n", + ")\n", + "from panoptica.utils.label_group import LabelGroup\n", + "from panoptica.utils.segmentation_class import SegmentationClassGroups" + ], + "id": "9a2ace58342d0470" + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "## 1. Vertebra Lesion Segmentation\n", + "\n", + "Vertebra lesions (spinal metastases) exhibit significant morphological heterogeneity, manifesting in diverse sizes, shapes, and textures across the different vertebral bodies (Cervical, Thoracic, Lumbar). Evaluating these lesions requires understanding their location relative to the specific vertebra they invade.\n", + "\n", + "The examined sample in this tutorial is adopted from a spinal metastasis dataset." + ], + "id": "76f2c283c365110" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-05-06T18:34:19.622573Z", + "start_time": "2026-05-06T18:34:19.612282Z" + } + }, + "cell_type": "code", + "source": [ + "data_dir = os.path.join(BASE_PATH, \"verteb_data\")\n", + "display(Image(filename=os.path.join(data_dir, \"vertebral_example.png\")))" + ], + "id": "bb1a7b8939c0cf42", + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + } + ], + "execution_count": 15 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "## 2. Load NIfTI Data\n", + "We load the reference lesion mask, predicted lesion mask, and the anatomical vertebra mask directly from the `./verteb_data` directory." + ], + "id": "7833dc161fcd745b" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-05-06T18:34:54.187174Z", + "start_time": "2026-05-06T18:34:32.517557Z" + } + }, + "cell_type": "code", + "source": [ + "ref_path = os.path.join(data_dir, \"reference.nii.gz\")\n", + "pred_path = os.path.join(data_dir, \"pred.nii.gz\")\n", + "anatomy_path = os.path.join(data_dir, \"verteb_segments.nii.gz\")\n", + "\n", + "ref_nii = nib.load(ref_path)\n", + "pred_nii = nib.load(pred_path)\n", + "anatomy_nii = nib.load(anatomy_path)\n", + "\n", + "ref_mask = ref_nii.get_fdata().astype(np.uint8)\n", + "pred_mask = pred_nii.get_fdata().astype(np.uint8)\n", + "verteb_anatomy = anatomy_nii.get_fdata().astype(np.uint8)\n", + "\n", + "# Extract voxel spacing from header for accurate distance metrics (like NSD/HD95)\n", + "voxelspacing = ref_nii.header.get_zooms()[:3]\n", + "\n", + "print(\"Data loaded successfully!\")\n", + "print(f\"Reference shape: {ref_mask.shape}, labels: {np.unique(ref_mask)}\")\n", + "print(f\"Prediction shape: {pred_mask.shape}, labels: {np.unique(pred_mask)}\")\n", + "print(f\"Anatomy labels: {np.unique(verteb_anatomy)}\")\n", + "print(f\"Voxel spacing: {voxelspacing}\")" + ], + "id": "5ccd64d4683fe6eb", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data loaded successfully!\n", + "Reference shape: (512, 512, 1031), labels: [0 1]\n", + "Prediction shape: (512, 512, 1031), labels: [0 1]\n", + "Anatomy labels: [ 0 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25]\n", + "Voxel spacing: (0.7246094, 0.7246094, 0.6)\n" + ] + } + ], + "execution_count": 16 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "## 3. Global Lesion Evaluation & Matching Strategies\n", + "\n", + "Vertebra lesions are often challenging for automatic segmentation due to their heterogeneity and small size. This makes them particularly challenging for **Global Panoptic Quality (PQ)** evaluation.\n", + "\n", + "We define a `SegmentationClassGroups` mapping to label 1.\n", + "We will compare three different matching strategies to highlight their impact on evaluation:\n", + "1. **Greedy 1:1 Matching (`NaiveThresholdMatching`)**: Iteratively pairs the first overlapping instances that beat the threshold. Can be suboptimal in dense lesion clusters.\n", + "2. **Optimal 1:1 Matching (`MaxBipartiteMatching`)**: Solves the global assignment problem to find the optimal 1:1 pairing that maximizes total IoU.\n", + "3. **Flexible N:1 Matching (`MaximizeMergeMatching`)**: Allows multiple fragmented predictions to merge and match a single ground-truth lesion, gracefully handling oversegmentation." + ], + "id": "57ff400e7373b54" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-05-06T18:36:31.003307Z", + "start_time": "2026-05-06T18:35:05.241965Z" + } + }, + "cell_type": "code", + "source": [ + "# Define the segmentation group (Label 1 = Lesion)\n", + "global_groups = SegmentationClassGroups({\"Lesion\": LabelGroup(1)})\n", + "\n", + "print(\"--- Greedy 1:1 Matching (NaiveThreshold, IoU > 0.1) ---\")\n", + "evaluator_naive = Panoptica_Evaluator(\n", + " expected_input=InputType.SEMANTIC,\n", + " instance_approximator=ConnectedComponentsInstanceApproximator(),\n", + " instance_matcher=NaiveThresholdMatching(\n", + " matching_metric=Metric.IOU, matching_threshold=0.1\n", + " ),\n", + " segmentation_class_groups=global_groups,\n", + ")\n", + "\n", + "res_naive_all = evaluator_naive.evaluate(\n", + " pred_mask, ref_mask, voxelspacing=voxelspacing, verbose=False\n", + ")\n", + "res_naive = res_naive_all.get(\"Lesion\", list(res_naive_all.values())[0])\n", + "\n", + "print(f\"PQ: {res_naive.pq:.4f} | SQ: {res_naive.sq:.4f} | RQ: {res_naive.rq:.4f}\")\n", + "print(f\"TP: {res_naive.tp} | FP: {res_naive.fp} | FN: {res_naive.fn}\\n\")\n", + "\n", + "\n", + "print(\"--- Optimal 1:1 Matching (MaxBipartite, IoU > 0.1) ---\")\n", + "evaluator_strict = Panoptica_Evaluator(\n", + " expected_input=InputType.SEMANTIC,\n", + " instance_approximator=ConnectedComponentsInstanceApproximator(),\n", + " instance_matcher=MaxBipartiteMatching(\n", + " matching_metric=Metric.IOU, matching_threshold=0.1\n", + " ),\n", + " segmentation_class_groups=global_groups,\n", + ")\n", + "\n", + "res_strict_all = evaluator_strict.evaluate(\n", + " pred_mask, ref_mask, voxelspacing=voxelspacing, verbose=False\n", + ")\n", + "res_strict = res_strict_all.get(\"Lesion\", list(res_strict_all.values())[0])\n", + "\n", + "print(f\"PQ: {res_strict.pq:.4f} | SQ: {res_strict.sq:.4f} | RQ: {res_strict.rq:.4f}\")\n", + "print(f\"TP: {res_strict.tp} | FP: {res_strict.fp} | FN: {res_strict.fn}\\n\")\n", + "\n", + "\n", + "print(\"--- Flexible N:1 Matching (MaximizeMerge, IoU > 0.1) ---\")\n", + "evaluator_flex = Panoptica_Evaluator(\n", + " expected_input=InputType.SEMANTIC,\n", + " instance_approximator=ConnectedComponentsInstanceApproximator(),\n", + " instance_matcher=MaximizeMergeMatching(\n", + " matching_metric=Metric.IOU, matching_threshold=0.1\n", + " ),\n", + " segmentation_class_groups=global_groups,\n", + ")\n", + "\n", + "res_flex_all = evaluator_flex.evaluate(\n", + " pred_mask, ref_mask, voxelspacing=voxelspacing, verbose=False\n", + ")\n", + "res_flex = res_flex_all.get(\"Lesion\", list(res_flex_all.values())[0])\n", + "\n", + "print(f\"PQ: {res_flex.pq:.4f} | SQ: {res_flex.sq:.4f} | RQ: {res_flex.rq:.4f}\")\n", + "print(f\"TP: {res_flex.tp} | FP: {res_flex.fp} | FN: {res_flex.fn}\")" + ], + "id": "71cbabd8af4b4ad3", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Greedy 1:1 Matching (NaiveThreshold, IoU > 0.1) ---\n", + "PQ: 0.4845 | SQ: 0.6784 | RQ: 0.7143\n", + "TP: 15 | FP: 8 | FN: 4\n", + "\n", + "--- Optimal 1:1 Matching (MaxBipartite, IoU > 0.1) ---\n", + "PQ: 0.4845 | SQ: 0.6784 | RQ: 0.7143\n", + "TP: 15 | FP: 8 | FN: 4\n", + "\n", + "--- Flexible N:1 Matching (MaximizeMerge, IoU > 0.1) ---\n", + "PQ: 0.5374 | SQ: 0.6807 | RQ: 0.7895\n", + "TP: 15 | FP: 4 | FN: 4\n" + ] + } + ], + "execution_count": 17 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## 4. Simple Semantic Segementation", + "id": "685c0e6da458775f" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-05-06T18:38:20.878622Z", + "start_time": "2026-05-06T18:38:05.534304Z" + } + }, + "cell_type": "code", + "source": [ + "evaluator = Panoptica_Evaluator(\n", + " expected_input=InputType.SEMANTIC,\n", + " instance_approximator=ConnectedComponentsInstanceApproximator(),\n", + " instance_matcher=NaiveThresholdMatching(),\n", + ")\n", + "\n", + "# print all results\n", + "result = evaluator.evaluate(pred_mask, ref_mask, verbose=False)[\"ungrouped\"]\n", + "print(result)" + ], + "id": "de80adaf1e6676f4", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "+++ MATCHING +++\n", + "Number of instances in reference (n_ref_instances): 19\n", + "Number of instances in prediction (n_pred_instances): 23\n", + "True Positives (tp): 14\n", + "False Positives (fp): 9\n", + "False Negatives (fn): 5\n", + "Recognition Quality / F1-Score (rq): 0.6666666666666666\n", + "\n", + "+++ GLOBAL +++\n", + "Global Binary Dice (global_bin_dsc): 0.8282655246252677\n", + "\n", + "+++ INSTANCE +++\n", + "Segmentation Quality IoU (sq): 0.7168009104019986 +- 0.13276536485497187\n", + "Panoptic Quality IoU (pq): 0.47786727360133235\n", + "Segmentation Quality Dsc (sq_dsc): 0.8281701852851214 +- 0.08906381781253059\n", + "Panoptic Quality Dsc (pq_dsc): 0.5521134568567476\n", + "Segmentation Quality ASSD (sq_assd): 0.7799511609336064 +- 0.4816085772137235\n", + "Segmentation Quality Relative Volume Difference (sq_rvd): -0.11475966334559162 +- 0.17423258730010882\n", + "\n" + ] + } + ], + "execution_count": 19 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "## 5. Region-Wise Anatomical Evaluation (Parts)\n", + "\n", + "When lesions span multiple vertebrae or are tightly packed, evaluating performance *locally* within each vertebra provides deeper clinical insight. Here, the individual vertebrae act as our **\"Parts\"**.\n", + "\n", + "We map the binary lesions to their corresponding anatomical segments. By creating a `LabelGroup` for each vertebra, Panoptica evaluates each region independently." + ], + "id": "f23d01ab96ef3333" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-05-06T18:42:32.082739Z", + "start_time": "2026-05-06T18:38:49.958360Z" + } + }, + "cell_type": "code", + "source": [ + "# Create anatomy-aware masks: Lesion voxels inherit the vertebra segment ID\n", + "ref_anatomy_mask = np.where(ref_mask == 1, verteb_anatomy, 0).astype(np.uint8)\n", + "pred_anatomy_mask = np.where(pred_mask == 1, verteb_anatomy, 0).astype(np.uint8)\n", + "\n", + "# Dynamically define a group for each unique anatomical segment present\n", + "unique_segments = np.unique(verteb_anatomy)\n", + "unique_segments = unique_segments[unique_segments > 0] # Ignore background\n", + "\n", + "segment_groups_dict = {}\n", + "for i in unique_segments:\n", + " # Ensure 'i' is converted from a NumPy type to a native Python integer.\n", + " # LabelGroup expects an int, and passing a numpy scalar causes an iterable TypeError under the hood.\n", + " segment_groups_dict[f\"Vertebra_{i}\"] = LabelGroup(int(i))\n", + "\n", + "regional_groups = SegmentationClassGroups(segment_groups_dict)\n", + "\n", + "evaluator_regional = Panoptica_Evaluator(\n", + " expected_input=InputType.SEMANTIC,\n", + " instance_approximator=ConnectedComponentsInstanceApproximator(),\n", + " instance_matcher=MaximizeMergeMatching(\n", + " matching_metric=Metric.IOU, matching_threshold=0.1\n", + " ),\n", + " segmentation_class_groups=regional_groups,\n", + ")\n", + "\n", + "results_regional = evaluator_regional.evaluate(\n", + " pred_anatomy_mask, ref_anatomy_mask, voxelspacing=voxelspacing, verbose=False\n", + ")\n", + "\n", + "print(\n", + " f\"{'Region':<12} | {'PQ':<6} | {'SQ':<6} | {'RQ':<6} | \"\n", + " f\"{'TP':<4} | {'FP':<4} | {'FN':<4}\"\n", + ")\n", + "print(\"-\" * 55)\n", + "for name, res in results_regional.items():\n", + " # Only print segments that actually have ground truth or predictions to keep it clean\n", + " if res.tp + res.fp + res.fn > 0:\n", + " print(\n", + " f\"{name:<12} | {res.pq:.4f} | {res.sq:.4f} | {res.rq:.4f} | \"\n", + " f\"{res.tp:<4} | {res.fp:<4} | {res.fn:<4}\"\n", + " )" + ], + "id": "ba322683ce2478bd", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Region | PQ | SQ | RQ | TP | FP | FN \n", + "-------------------------------------------------------\n", + "vertebra_11 | 0.5290 | 0.5290 | 1.0000 | 1 | 0 | 0 \n", + "vertebra_14 | 0.9136 | 0.9136 | 1.0000 | 2 | 0 | 0 \n", + "vertebra_15 | 0.5344 | 0.5344 | 1.0000 | 1 | 0 | 0 \n", + "vertebra_17 | 0.3027 | 0.5044 | 0.6000 | 3 | 1 | 3 \n", + "vertebra_18 | 0.8938 | 0.8938 | 1.0000 | 1 | 0 | 0 \n", + "vertebra_21 | 0.7043 | 0.7043 | 1.0000 | 2 | 0 | 0 \n", + "vertebra_22 | 0.3949 | 0.5923 | 0.6667 | 1 | 0 | 1 \n", + "vertebra_23 | 0.6420 | 0.6420 | 1.0000 | 1 | 0 | 0 \n", + "vertebra_24 | 0.5238 | 0.7856 | 0.6667 | 2 | 2 | 0 \n", + "vertebra_25 | 0.6346 | 0.9519 | 0.6667 | 1 | 1 | 0 \n" + ] + } + ], + "execution_count": 20 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": [ + "## 6. Threshold Analysis and AUTC\n", + "\n", + "Spinal lesions can be very small, meaning a shift of just 1-2 voxels causes IoU to plummet. Instead of relying on a single, arbitrary threshold, we sweep the threshold and calculate the **Area Under Threshold Curve (AUTC)**: $AUTC = \\int_{0}^{1} PQ(\\tau) d\\tau$. This provides a highly robust metric for overall performance." + ], + "id": "bedbd210470089f" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-05-06T18:54:22.207626Z", + "start_time": "2026-05-06T18:43:56.406587Z" + } + }, + "cell_type": "code", + "source": [ + "thresholds = np.arange(0.05, 1.0, 0.05)\n", + "pq_scores = []\n", + "tp_counts = []\n", + "\n", + "print(\"Sweeping thresholds for Global Lesion Evaluation...\")\n", + "for thresh in thresholds:\n", + " matcher = MaximizeMergeMatching(\n", + " matching_metric=Metric.IOU, matching_threshold=float(thresh)\n", + " )\n", + "\n", + " ev = Panoptica_Evaluator(\n", + " expected_input=InputType.SEMANTIC,\n", + " instance_approximator=ConnectedComponentsInstanceApproximator(),\n", + " instance_matcher=matcher,\n", + " segmentation_class_groups=global_groups,\n", + " )\n", + "\n", + " r_all = ev.evaluate(pred_mask, ref_mask, voxelspacing=voxelspacing, verbose=False)\n", + " r = r_all.get(\"Lesion\", list(r_all.values())[0])\n", + "\n", + " pq_scores.append(r.pq)\n", + " tp_counts.append(r.tp)\n", + " print(f\" [IoU >= {thresh:.2f}] PQ={r.pq:.4f} | TP={r.tp}\")\n", + "\n", + "# Calculate Area Under the Curve (using trapezoidal rule from sklearn)\n", + "autc_score = auc(thresholds, pq_scores)\n", + "\n", + "# Plotting the degradation curves and AUTC\n", + "fig, ax1 = plt.subplots(figsize=(10, 5))\n", + "\n", + "color = \"tab:blue\"\n", + "ax1.set_xlabel(\"Decision Threshold (IoU)\", fontsize=12)\n", + "ax1.set_ylabel(\"Panoptic Quality (PQ)\", color=color, fontsize=12)\n", + "ax1.plot(thresholds, pq_scores, marker=\"o\", color=color, linewidth=2)\n", + "ax1.fill_between(thresholds, pq_scores, alpha=0.2, color=color) # Fill for AUTC visual\n", + "ax1.tick_params(axis=\"y\", labelcolor=color)\n", + "ax1.grid(True, linestyle=\"--\", alpha=0.6)\n", + "\n", + "ax2 = ax1.twinx()\n", + "color = \"tab:red\"\n", + "ax2.set_ylabel(\"True Positives (TP)\", color=color, fontsize=12)\n", + "ax2.plot(thresholds, tp_counts, marker=\"s\", linestyle=\"--\", color=color, linewidth=2)\n", + "ax2.tick_params(axis=\"y\", labelcolor=color)\n", + "\n", + "fig.tight_layout()\n", + "plt.title(\n", + " f\"Impact of Matching Threshold on Detection\\nAUTC = {autc_score:.4f}\",\n", + " fontweight=\"bold\",\n", + ")\n", + "plt.show()\n", + "\n", + "print(f\"Final AUTC Score: {autc_score:.4f}\")\n", + "print(\n", + " \"AUTC captures the model's true performance spectrum, proving highly robust against \"\n", + " \"the tiny-instance penalty.\"\n", + ")" + ], + "id": "3b74694a8cc7f5e2", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sweeping thresholds for Global Lesion Evaluation...\n", + " [IoU >= 0.05] PQ=0.5374 | TP=15\n", + " [IoU >= 0.10] PQ=0.5374 | TP=15\n", + " [IoU >= 0.15] PQ=0.5300 | TP=14\n", + " [IoU >= 0.20] PQ=0.5300 | TP=14\n", + " [IoU >= 0.25] PQ=0.5300 | TP=14\n", + " [IoU >= 0.30] PQ=0.5300 | TP=14\n", + " [IoU >= 0.35] PQ=0.5300 | TP=14\n", + " [IoU >= 0.40] PQ=0.5300 | TP=14\n", + " [IoU >= 0.45] PQ=0.5300 | TP=14\n", + " [IoU >= 0.50] PQ=0.5300 | TP=14\n", + " [IoU >= 0.55] PQ=0.4743 | TP=12\n", + " [IoU >= 0.60] PQ=0.4432 | TP=11\n", + " [IoU >= 0.65] PQ=0.4094 | TP=10\n", + " [IoU >= 0.70] PQ=0.2092 | TP=5\n", + " [IoU >= 0.75] PQ=0.2092 | TP=5\n", + " [IoU >= 0.80] PQ=0.1719 | TP=4\n", + " [IoU >= 0.85] PQ=0.1719 | TP=4\n", + " [IoU >= 0.90] PQ=0.0870 | TP=2\n", + " [IoU >= 0.95] PQ=0.0000 | TP=0\n" + ] + }, + { + "data": { + "text/plain": [ + "
" + ], + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Final AUTC Score: 0.3611\n", + "AUTC captures the model's true performance spectrum, proving highly robust against the tiny-instance penalty.\n" + ] + } + ], + "execution_count": 21 + } + ], + "metadata": { + "kernelspec": { + "name": "python3", + "language": "python", + "display_name": "Python 3 (ipykernel)" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/panoptica/verteb_data/pred.nii.gz b/panoptica/verteb_data/pred.nii.gz new file mode 100644 index 0000000..7637591 Binary files /dev/null and b/panoptica/verteb_data/pred.nii.gz differ diff --git a/panoptica/verteb_data/reference.nii.gz b/panoptica/verteb_data/reference.nii.gz new file mode 100644 index 0000000..b552909 Binary files /dev/null and b/panoptica/verteb_data/reference.nii.gz differ diff --git a/panoptica/verteb_data/verteb_segments.nii.gz 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