Distribution Matching Losses Can Hallucinate Features in Medical Image Translation
@article{Cohen2018DistributionML, title={Distribution Matching Losses Can Hallucinate Features in Medical Image Translation}, author={Joseph Paul Cohen and Margaux Luck and Sina Honari}, journal={ArXiv}, year={2018}, volume={abs/1805.08841}, url={https://api.semanticscholar.org/CorpusID:43919703} }
This paper discusses how distribution matching losses, such as those used in CycleGAN, when used to synthesize medical images can lead to mis-diagnosis of medical conditions. It seems appealing to…
Topics
Translation Output (opens in a new tab)Translated Images (opens in a new tab)Medical Images (opens in a new tab)Transformed Images (opens in a new tab)Paired Data (opens in a new tab)Medical Image Translation (opens in a new tab)Uncertainty (opens in a new tab)CycleGAN (opens in a new tab)Image Translation Models (opens in a new tab)
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