AgileFormer: A Spatially Agile Transformer UNet for Efficient Medical Image Segmentation

The core message of this paper is to introduce a novel spatially agile transformer UNet architecture, termed AgileFormer, that systematically incorporates deformable patch embedding, spatially dynamic self-attention, and multi-scale deformable positional encoding to effectively capture diverse target objects in medical image segmentation tasks.