LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation

arXiv:2403.05246v1 Announce Type: cross
Abstract: UNet and its variants have been widely used in medical image segmentation. However, these models, especially those based on Transformer architectures, pose challenges due to their large number of parameters and computational loads, making them unsuitable for mobile health applications. Recently, State Space Models (SSMs), exemplified by Mamba, have emerged as competitive alternatives to CNN and Transformer architectures. Building upon this, we employ Mamba as a lightweight substitute for CNN and Transformer within UNet, aiming …

arxiv cs.cv eess.iv image mamba medical segmentation type unet