BUSI
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Medical Image Segmentation | BUSI (test) | Dice91.47 | 121 | |
| Medical Image Classification | BUSI | Accuracy89.7 | 88 | |
| Medical Image Segmentation | BUSI | Dice Score90.6 | 61 | |
| Anomaly Detection | BUSI (test) | AUROC (Image)91 | 32 | |
| Anomaly Localization | BUSI (test) | Pixel AUROC0.901 | 28 | |
| Image Denoising | BUSI | PSNR36.5392 | 24 | |
| Object Detection | BUSI | AP@0.5 (BN)78.3 | 19 | |
| Anomaly Detection | BUSI | AUROC91.4 | 16 | |
| Anomaly Localization | BUSI | AUROC (pixel-level)91.8 | 16 | |
| Anomaly Classification | BUSI | AUROC73.8 | 15 | |
| Ultrasound Image Segmentation | BUSI 1.0 (test) | Dice86.52 | 14 | |
| Breast Cancer Segmentation | BUSI 129 (1/4) labels | DSC (Benign)74.01 | 14 | |
| Breast Cancer Segmentation | BUSI 64 (1/8) labels | DSC (Benign)71.87 | 14 | |
| Medical Image Classification | BUSI (test) | Accuracy90.2 | 14 | |
| Adversarial Attack | BUSI (five-fold cross-validation) | Success Rate100 | 12 | |
| Medical Diagnosis Classification | BUSI | F1 Score90.5 | 12 | |
| Medical Image Segmentation | BUSI (three fixed-seed random data splits) | mIoU0.6614 | 8 | |
| Medical Image Segmentation | BUSI | Latency (ms)3.06 | 6 | |
| Lesion Detection | BUSI | Training Time (m)3.2 | 6 | |
| Medical Image Segmentation | BUSI 4 | F1 Score79.37 | 6 | |
| Medical Image Segmentation | BUSI (val) | Metric- | 0 |
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