SMAFormer: Synergistic Multi-Attention Transformer for Medical Image Segmentation 事件

SMAFormer: Synergistic Multi-Attention Transformer for Medical Image Segmentation arXiv:2409.00346v5 Announce Type: replace Abstract: In medical image segmentation, specialized computer vision techniques, notably transformers grounded in attention mechanisms and residual networks employing skip connections, have been instrumental in advancing performance. Nonetheless, previous models often falter when segmenting small, irregularly shaped tumors. To this end, we introduce SMAFormer, an efficient