MSLAU-Net proposes a hybrid CNN-Transformer architecture using multi-scale linear attention and lightweight top-down aggregation that outperforms prior methods on medical segmentation benchmarks across three modalities.
Hatamizadeh et al.,Unetr: Transformers for 3d medical image segmentation,Proceedings of the IEEE/CVF winter conference on applications of computer vision, 2022, 574–584
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MSLAU-Net: A Hybrid CNN-Transformer Network for Medical Image Segmentation
MSLAU-Net proposes a hybrid CNN-Transformer architecture using multi-scale linear attention and lightweight top-down aggregation that outperforms prior methods on medical segmentation benchmarks across three modalities.