## Dataset004_PICAI Task: Multi-class prostate segmentation (prostate gland + tumor) on prostate MRI (T2W, ADC, HBV) + ISUP grade classification (6-class: 0=Benign/Indolent, 1–5=ISUP grades) ### Per-Fold Results — Segmentation | Fold | DSC (prostate) | NSD (prostate) | DSC (tumor) | NSD (tumor) | DSC mean | NSD mean | |------|----------------|----------------|-------------|-------------|----------|----------| | 0 | 0.960 | 0.959 | 0.473 | 0.490 | 0.717 | 0.724 | | 1 | 0.960 | 0.960 | 0.536 | 0.552 | 0.748 | 0.756 | | 2 | 0.959 | 0.959 | 0.634 | 0.649 | 0.797 | 0.804 | | 3 | 0.947 | 0.939 | 0.168 | 0.188 | 0.558 | 0.564 | | 4 | 0.960 | 0.960 | 0.557 | 0.575 | 0.759 | 0.767 | | **Mean** | **0.957** | **0.955** | **0.474** | **0.491** | **0.716** | **0.723** | | **Std** | **0.006** | **0.009** | **0.180** | **0.179** | **0.093** | **0.094** | ### Per-Fold Results — Classification | Fold | AUROC | AUPRC | Bal Acc | F1 | |------|-------|-------|---------|------| | 0 | 0.731 | 0.290 | 0.240 | 0.236 | | 1 | 0.720 | 0.281 | 0.212 | 0.183 | | 2 | 0.746 | 0.300 | 0.240 | 0.229 | | 3 | 0.702 | 0.310 | 0.176 | 0.063 | | 4 | 0.736 | 0.350 | 0.263 | 0.224 | | **Mean** | **0.727** | **0.306** | **0.226** | **0.187** | | **Std** | **0.017** | **0.027** | **0.033** | **0.072** | **Notes:** - Prostate gland segmentation is strong and consistent (DSC 0.957 ± 0.006); the gland is a well-defined, large structure - Tumor segmentation is challenging (DSC 0.474 ± 0.180): 71% of cases (1075/1500) have no tumor, so many folds see near-zero tumor Dice dominated by true-negatives - Fold 3 has noticeably lower tumor DSC (0.168) and NSD (0.188), likely due to an unfavorable fold split or harder cases - Classification: AUROC 0.727 is reasonable for 6-class ISUP grading; Bal Acc (0.226) and F1 (0.187) are near the random baseline (1/6 ≈ 0.167), driven by severe class imbalance (847/1500 cases are grade 0) ### Figures ![Box plots](figures/01_boxplot_dsc_nsd.png) ![Case sampling](figures/02_case_sampling.png) ![ROC/PRC](figures/03_roc_prc.png) ![Confusion matrix](figures/04_confusion_matrix.png) ![FP/FN cases](figures/05_fp_fn_cases.png)