| { |
| "archive_metadata": { |
| "archive_name": "Attention-Gated 3D U-Net Final Evaluation Reference", |
| "created_utc": "2026-09-06T00:34:32.152419+00:00", |
| "evaluation_block": "Block 13", |
| "archive_block": "Block 14", |
| "status": "FINAL_ATTENTION_REFERENCE" |
| }, |
| "repository": { |
| "huggingface_repo": "Reduanul1997/RepositoryAttention3DUNet", |
| "repo_type": "model" |
| }, |
| "model": { |
| "name": "Attention3DUNet", |
| "architecture": "Attention-Gated 3D U-Net", |
| "input_channels": 4, |
| "output_classes": 4, |
| "parameters": 5669856 |
| }, |
| "dataset": { |
| "dataset": "BraTS2020", |
| "modalities": [ |
| "FLAIR", |
| "T1", |
| "T1ce", |
| "T2" |
| ], |
| "classes": [ |
| "Background", |
| "NCR/NET", |
| "Edema", |
| "Enhancing Tumor" |
| ], |
| "training_patients": 294, |
| "validation_patients": 74, |
| "patch_size": [ |
| 64, |
| 64, |
| 64 |
| ] |
| }, |
| "model_selection": { |
| "best_model_epoch": 34, |
| "best_validation_dice_from_training": 0.764262, |
| "note": "This is the validation Dice reported by the training pipeline and used for model selection. It is distinct from the independently recomputed full-validation confusion-matrix metrics." |
| }, |
| "evaluation_reference": { |
| "foreground_macro": { |
| "dice": 0.724903, |
| "iou": 0.578467, |
| "precision": 0.76502, |
| "recall": 0.6984 |
| }, |
| "tumor_binary": { |
| "dice": 0.911371, |
| "iou": 0.837173, |
| "precision": 0.926928, |
| "recall": 0.896327, |
| "sensitivity": 0.896327, |
| "false_negative_rate": 0.103673, |
| "false_positive_rate": 0.021416, |
| "TP": 4044236, |
| "TN": 14567831, |
| "FP": 318815, |
| "FN": 467774 |
| }, |
| "per_class": { |
| "Unknown": { |
| "Model": "Attention3DUNet", |
| "Best_Model_Epoch": 34.0, |
| "Class_ID": 3.0, |
| "Class_Name": "Enhancing Tumor", |
| "Dice": 0.8116382728647753, |
| "IoU": 0.68298924000303, |
| "Precision": 0.8477082780883921, |
| "Recall": 0.7785125474484258, |
| "Sensitivity": 0.7785125474484258, |
| "FNR": 0.2214874525515647, |
| "FPR": 0.0081125672772594, |
| "TP": 827966.0, |
| "TN": 18186388.0, |
| "FP": 148745.0, |
| "FN": 235557.0 |
| } |
| } |
| }, |
| "baseline_comparison_policy": { |
| "primary_segmentation_metric": "Foreground Macro Dice", |
| "secondary_segmentation_metrics": [ |
| "Foreground Macro IoU", |
| "Foreground Macro Precision", |
| "Foreground Macro Recall" |
| ], |
| "primary_fn_metric": "Tumor False Negative Rate (FNR)", |
| "additional_fn_metric": "Tumor False Negatives (FN)", |
| "comparison_rule": "Future models must be evaluated using the same validation split, preprocessing, class definitions, tumor-vs-background definition, and metric calculation procedure before direct comparison with this model." |
| }, |
| "baseline_vs_attention_comparison": { |
| "baseline_model": { |
| "name": "Baseline 3D U-Net", |
| "repository": "Reduanul1997/RepositoryBaseLine3DuNet", |
| "parameters": 22580964, |
| "best_epoch": 45, |
| "best_training_dice": 0.772125, |
| "foreground_macro_dice": 0.757824, |
| "foreground_macro_iou": 0.618727, |
| "foreground_macro_precision": 0.781685, |
| "foreground_macro_recall": 0.740964, |
| "tumor_dice": 0.927715, |
| "tumor_iou": 0.865175, |
| "tumor_precision": 0.942361, |
| "tumor_recall": 0.913516, |
| "tumor_fnr": 0.086484, |
| "tumor_fpr": 0.017968, |
| "tumor_tp": 4312069, |
| "tumor_tn": 14414613, |
| "tumor_fp": 263746, |
| "tumor_fn": 408228 |
| }, |
| "attention_model": { |
| "name": "Attention-Gated 3D U-Net", |
| "repository": "Reduanul1997/RepositoryAttention3DUNet", |
| "parameters": 5669856, |
| "best_epoch": 34, |
| "best_training_dice": 0.764262, |
| "foreground_macro_dice": 0.724903, |
| "foreground_macro_iou": 0.578467, |
| "foreground_macro_precision": 0.76502, |
| "foreground_macro_recall": 0.6984, |
| "tumor_dice": 0.911371, |
| "tumor_iou": 0.837173, |
| "tumor_precision": 0.926928, |
| "tumor_recall": 0.896327, |
| "tumor_fnr": 0.103673, |
| "tumor_fpr": 0.021416, |
| "tumor_tp": 4044236, |
| "tumor_tn": 14567831, |
| "tumor_fp": 318815, |
| "tumor_fn": 467774 |
| }, |
| "interpretation": { |
| "parameter_reduction_percent": 74.89099225347509, |
| "foreground_macro_dice_difference": -0.03292100000000009, |
| "tumor_fnr_difference": 0.017188999999999996, |
| "tumor_fn_difference": 59546, |
| "best_foreground_macro_dice": "Baseline 3D U-Net", |
| "best_tumor_fnr": "Baseline 3D U-Net", |
| "most_parameter_efficient": "Attention-Gated 3D U-Net", |
| "conclusion": "The Attention-Gated 3D U-Net is substantially more parameter-efficient, but the Baseline 3D U-Net achieves better segmentation and lower tumor false-negative performance on the current validation set." |
| } |
| }, |
| "artifact_files": [ |
| "attention_evaluation_results.json", |
| "attention_evaluation_metrics.csv", |
| "attention_per_class_metrics.csv", |
| "attention_multiclass_confusion_matrix.png", |
| "attention_tumor_background_confusion_matrix.png", |
| "attention_final_evaluation_summary.json", |
| "baseline_vs_attention_comparison.json", |
| "baseline_vs_attention_comparison.csv", |
| "attention_final_evaluation_package.zip" |
| ] |
| } |
