| { |
| "model_name": "DenseNet3DSmooth", |
| "preprocessor_name": null, |
| "model_params": { |
| "in_channels_ct": 1, |
| "in_channels_dose": 1, |
| "in_channels_mask": 1, |
| "drop_rate": 0.3, |
| "use_skip_connections": true, |
| "arch": [4, 4, 4], |
| "stem_out_channels_total": 96, |
| "growth_rate": 32, |
| "batch_norm_dose": true |
| }, |
| "model_preprocessing": { |
| "type_order": ["dose", "mask", "ct"], |
| "modality": { |
| "dose": { |
| "extract": false, |
| "normalization_value": 70.0, |
| "description": "Physical dose, normalized by the prescription." |
| }, |
| "ct": { |
| "window": [-1000, 1000], |
| "description": "CT in Hounsfield units, windowed to [-1000, 1000]." |
| }, |
| "mask": { |
| "collapse": true, |
| "description": "Binary structure mask (collapsed to a single channel)." |
| } |
| }, |
| "input_dimensions": [100, 100, 40], |
| "input_spacing": [3.0, 3.0, 2.5], |
| "center": "target" |
| }, |
| "metadata": { |
| "description": "DenseNet3DSmooth NTCP outcome model for the TG119 proton phantom.", |
| "training": { |
| "dataset": "tg119", |
| "modality": "protons", |
| "input_resolution_mm": [3.0, 3.0, 2.5], |
| "notes": "Dose-preserving DenseNet3D (BatchNorm, anti-aliased pooling); dose normalized by 70 Gy prescription." |
| }, |
| "model_input": { |
| "type_order": ["dose", "mask", "ct"], |
| "tensor_shapes": { |
| "dose": [1, 100, 100, 40], |
| "ct": [1, 100, 100, 40], |
| "mask": [1, 100, 100, 40] |
| } |
| } |
| } |
| } |
|
|
