Sep 2026
A multi-scale transformer U-Net with SECA attention for robust breast tumor segmentation across diverse imaging modalities
A novel Swin Transformer–based U-Net architecture whose primary contribution lies in a Swin-Enhanced Cross Attention (SECA)-driven decoding strategy, rather than the use of a Swin encoder alone, is proposed.
Reza Ahmadi Lashaki, Farhad Bayrami, Shayan Rokhva et al.
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