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…very; bump 0.9.2 - vision_patch: PatchInferenceEngine/patch_inference accept a list of models and soft-vote per-patch probabilities in one sliding-window pass; AMP forward pass uses bfloat16; keep_largest_component skipped for multi-class; empty model-list guarded - vision_metrics: calculate_all_metrics and evaluate_segmentations per-case panel with spacing-aware ASSD/HD95/NSD read from a single ground-truth LabelMap - utils: find_fold_learners discovers per-fold best_learner.pkl from an MLflow experiment; log_metrics_table strips non-finite values before logging - vision_loss: DynUNetDSAdapter adapts DynUNet deep-supervision output to the list DeepSupervisionLoss expects - tutorials 12b/12c updated for cross-validation and soft-vote ensemble inference - bump version 0.9.1 -> 0.9.2
…workflow - 01_five_fold_cross_validation.ipynb: 5-fold cross-validation over UNet, DynUNet and a SegMamba fork on the patch-based workflow - 02_inference_new_cases.ipynb: 5-fold soft-vote ensemble inference on new cases - ml_dataset.csv (346 CE-T1w cases with pre-assigned folds), README, inference config JSON - gitignore: preprocessed/ and cv_results_*/ notebook run byproducts
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