Aug. 16, 2022, 1:14 a.m. | Xi Jia, Joseph Bartlett, Tianyang Zhang, Wenqi Lu, Zhaowen Qiu, Jinming Duan

cs.CV updates on arXiv.org arxiv.org

Due to their extreme long-range modeling capability, vision transformer-based
networks have become increasingly popular in deformable image registration. We
believe, however, that the receptive field of a 5-layer convolutional U-Net is
sufficient to capture accurate deformations without needing long-range
dependencies. The purpose of this study is therefore to investigate whether
U-Net-based methods are outdated compared to modern transformer-based
approaches when applied to medical image registration. For this, we propose a
large kernel U-Net (LKU-Net) by embedding a parallel convolutional block …

arxiv image medical registration transformer

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