An Asymetric Cycle-Consistency Loss for Dealing with Many-to-One Mappings in Image Translation: A Study on Thigh MR Scans

23 Apr 2020Michael GadermayrMaximilian TschuchnigLaxmi GuptaDorit MerhofNils KrämerDaniel TruhnBurkhard Gess

Generative adversarial networks using a cycle-consistency loss facilitate unpaired training of image-translation models and thereby exhibit a very high potential in manifold medical applications. However, the fact that images in one domain potentially map to more than one image in another domain (e.g. in case of pathological changes) exhibits a major challenge for training the networks... (read more)

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