{
  "model_name": "Pulmo",
  "description": "Two-stage explainable lung-nodule analysis pipeline on LUNA16/LIDC-IDRI: a 3D detector finds nodule centres, a 2.5D concept-bottleneck model characterises each candidate (detection, malignancy, 8 radiological concepts, segmentation).",
  "pipeline": ["stage1_detector", "stage2_characteriser"],

  "stage1_detector": {
    "architecture": "HeatmapUNet3D",
    "weights": "stage1_detector_v2.pth",
    "role": "Locate nodule centres in a full CT volume (3D sliding window -> centre heatmap -> peaks).",
    "base_channels": 16,
    "patch_zyx": [64, 128, 128],
    "input": "(B, 1, 64, 128, 128) float32 in [0, 1] (native resolution, no downsampling)",
    "output": "(B, 1, 64, 128, 128) per-voxel nodule-centre probability heatmap",
    "loss": "CenterNet penalty-reduced focal loss",
    "metrics_scan_level": {
      "CPM_at_8FP": 0.629,
      "sensitivity_at_16FP_per_scan": 0.956,
      "mean_centre_distance_mm": 1.85,
      "note": "FROC on held-out internal val split. Operating point is tunable via peak_thresh; Stage 2 filters false positives."
    }
  },

  "stage2_characteriser": {
    "architecture": "Student2p5D",
    "weights": "student_2p5d_best.pth",
    "role": "Per-candidate diagnosis + explanation from a 64^3 patch (its 7 central axial slices).",
    "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"
    ],
    "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
    }
  },

  "preprocessing": {
    "hu_clip": [-1000, 1000],
    "normalize": "(x - hu_min) / (hu_max - hu_min)  -> [0, 1]   (identical for both stages)",
    "stage1_input": "raw (Z, Y, X) HU volume; sliding-window 3D patches of [64, 128, 128]",
    "stage2_input": "7 central axial slices of a 64^3 patch centred on a Stage-1 candidate",
    "spacing_order": "[z, y, x] in mm"
  },

  "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"
}