For image segmentation, the current standard is to perform pixel-level optimization and inference in Euclidean output embedding spaces through linear hyperplanes. In this work, we show that hyperbolic ...

State Space Models (SSMs), especially Mamba, have shown great promise in medical image segmentation due to their ability to model long-range dependencies with linear computational complexity. However, ...

SegFormer3D An Efficient Transformer for 3D Medical Image Segmentation Segformer3D is a light-weight and efficient hierarchical Transformer designed for 3D volumetric segmentation. It calculates ...

Compared with natural image segmentation, small sample image segmentation tasks, such as medical image segmentation and defect detection, have been less studied. Recent studies made efforts on ...