Feb. 27, 2024, 5:48 a.m. | Abdullah Nazib, Riad Hassan, Zahidul Islam, Clinton Fookes

cs.CV updates on arXiv.org arxiv.org

arXiv:2303.10796v2 Announce Type: replace-cross
Abstract: Organ at risk (OAR) segmentation in computed tomography (CT) imagery is a difficult task for automated segmentation methods and can be crucial for downstream radiation treatment planning. U-net has become a de-facto standard for medical image segmentation and is frequently used as a common baseline in medical image segmentation tasks. In this paper, we propose a multiple decoder U-net architecture and use the segmentation disagreement between the decoders as attention to the bottleneck of the …

abstract arxiv attention automated become cs.cv eess.iv image medical planning risk segmentation standard treatment type uncertainty

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