Prostate Cancer Detection on Prostate MRI dataset
91.7AUCOurs (HOG+SVM)
Evaluation Results
| Method | Links | |
|---|---|---|
| Ours (HOG+SVM)Year=2026, Dataset Size=162 images, Input Type=T2-only, Model Type=Classical ML, Evaluation Level=Image-level, csPCa Prevalence=64% (102/162), Parameters=Minimal2026.03 | 91.7 | |
| Ours (ResNet18)Year=2026, Dataset Size=162 images, Input Type=T2-only, Model Type=Transfer CNN, Evaluation Level=Image-level, csPCa Prevalence=64% (102/162), Parameters=11M2026.03 | 90.5 | |
| Hamm et al. [9]Year=2023, Dataset Size=1,224, Input Type=bp-MRI (T2+DWI), Model Type=Explainable DL (XAI), Evaluation Level=Lesion-level, csPCa Prevalence=~49%2026.03 | 89 | |
| Li et al. [13]Year=2025, Dataset Size=1,476, Input Type=bp-MRI (T2+DWI), Model Type=CSwin Transformer, Evaluation Level=Patient-level, csPCa Prevalence=~38% (PI-CAI), Parameters=80M+2026.03 | 89 |