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Contrastive Registration for Unsupervised Medical Image Segmentation
[article]
2022
arXiv
pre-print
Medical image segmentation is a relevant task as it serves as the first step for several diagnosis processes, thus it is indispensable in clinical usage. Whilst major success has been reported using supervised techniques, they assume a large and well-representative labelled set. This is a strong assumption in the medical domain where annotations are expensive, time-consuming, and inherent to human bias. To address this problem, unsupervised techniques have been proposed in the literature yet it
arXiv:2011.08894v3
fatcat:2lmsahntrrf4jjlifioplcjx2a