March 21, 2024, 4:45 a.m. | Renkai Wu, Yinghao Liu, Pengchen Liang, Qing Chang

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.13642v1 Announce Type: new
Abstract: In the field of medical image segmentation, variant models based on Convolutional Neural Networks (CNNs) and Visual Transformers (ViTs) as the base modules have been very widely developed and applied. However, CNNs are often limited in their ability to deal with long sequences of information, while the low sensitivity of ViTs to local feature information and the problem of secondary computational complexity limit their development. Recently, the emergence of state-space models (SSMs), especially 2D-selective-scan (SS2D), …

arxiv cs.cv image mamba medical segmentation type unet vision

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