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TransNorm: Transformer Provides a Strong Spatial Normalization Mechanism for a Deep Segmentation Model. (arXiv:2207.13415v1 [cs.CV])
July 28, 2022, 1:12 a.m. | Reza Azad, Mohammad T. AL-Antary, Moein Heidari, Dorit Merhof
cs.CV updates on arXiv.org arxiv.org
In the past few years, convolutional neural networks (CNNs), particularly
U-Net, have been the prevailing technique in the medical image processing era.
Specifically, the seminal U-Net, as well as its alternatives, have successfully
managed to address a wide variety of medical image segmentation tasks. However,
these architectures are intrinsically imperfect as they fail to exhibit
long-range interactions and spatial dependencies leading to a severe
performance drop in the segmentation of medical images with variable shapes and
structures. Transformers, preliminary proposed …
More from arxiv.org / cs.CV updates on arXiv.org
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