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"model_name": "Pulmo",
"architecture": "Student2p5D",
"description": "2.5D concept-bottleneck multi-task model for lung nodule analysis, distilled from a 3D teacher.",
"input": {
"n_slices": 7,
"slice_size": [64, 64],
"tensor_shape": "(B, 7, 64, 64)",
"dtype": "float32",
"value_range": [0.0, 1.0]
},
"backbone": {
"type": "UNet2D",
"base_channels": 24,
"trunk_dim": 384
},
"heads": {
"detection": "2 (nodule vs non-nodule)",
"concepts": "8 (LIDC radiological concepts, regression)",
"malignancy": "Linear(8 -> 2), concept bottleneck",
"segmentation": "(B, 1, 64, 64), middle axial slice"
},
"n_concepts": 8,
"concept_names": [
"subtlety", "internalStructure", "calcification", "sphericity",
"margin", "lobulation", "spiculation", "texture"
],
"preprocessing": {
"roi_size_3d": [64, 64, 64],
"hu_clip": [-1000, 1000],
"normalize": "(x - hu_min) / (hu_max - hu_min) -> [0, 1]",
"slice_extraction": "take the 7 central axial slices of a 64^3 patch centered on the candidate (z in [29, 36))"
},
"test_metrics_patch_level": {
"detection_auc": 0.997,
"malignancy_auc": 0.986,
"segmentation_dice": 0.859,
"note": "Held-out internal test split (patient-level split of LUNA16). Not externally validated."
},
"teacher_reference_3d": {
"detection_auc": 0.998,
"malignancy_auc": 0.986,
"segmentation_dice": 0.857
},
"training_data": "LUNA16 (subset of LIDC-IDRI), 888 scans, patient-level 80/10/10 split",
"license": "cc-by-4.0",
"intended_use": "research only; not a medical device"
}
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