Attn U-Net + Multi-Input + FTL

Reported on 2 benchmarks across 1 task · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical2 results

Medical Image SegmentationonISIC 2018
mean Dice· 2018-10-18
0.856
best: 0.9253 (Polar Res-U-Net++)
SOTA
A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation arXiv:1810.07842
Medical Image SegmentationonBUS 2017 Dataset B
Dice Score· 2018-10-18
0.804
SOTA
A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation arXiv:1810.07842