UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation

arXiv:2212.04497v3 Announce Type: replace
Abstract: Owing to the success of transformer models, recent works study their applicability in 3D medical segmentation tasks. Within the transformer models, the self-attention mechanism is one of the main building blocks that strives to capture long-range dependencies. However, the self-attention operation has quadratic complexity which proves to be a computational bottleneck, especially in volumetric medical imaging, where the inputs are 3D with numerous slices. In this paper, we propose a 3D medical image segmentation approach, …

arxiv cs.cv image medical segmentation type