H2MaT-Unet:Hierarchical hybrid multi-axis transformer based Unet for medical image segmentation.

Accurate segmentation and lesion localization are essential for treating diseases in medical images. Despite deep learning methods enhancing segmentation, they still have limitations due to convolutional neural networks' inability to capture long-range feature dependencies. The self-attention mechanism in Transformers addresses this drawback, but high-resolution images present computational complexity.