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- W2890139949 endingPage "101552" @default.
- W2890139949 startingPage "101552" @default.
- W2890139949 abstract "Generative adversarial networks have gained a lot of attention in the computer vision community due to their capability of data generation without explicitly modelling the probability density function. The adversarial loss brought by the discriminator provides a clever way of incorporating unlabeled samples into training and imposing higher order consistency. This has proven to be useful in many cases, such as domain adaptation, data augmentation, and image-to-image translation. These properties have attracted researchers in the medical imaging community, and we have seen rapid adoption in many traditional and novel applications, such as image reconstruction, segmentation, detection, classification, and cross-modality synthesis. Based on our observations, this trend will continue and we therefore conducted a review of recent advances in medical imaging using the adversarial training scheme with the hope of benefiting researchers interested in this technique." @default.
- W2890139949 created "2018-09-27" @default.
- W2890139949 creator A5006921976 @default.
- W2890139949 creator A5017986343 @default.
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- W2890139949 date "2019-12-01" @default.
- W2890139949 modified "2023-10-18" @default.
- W2890139949 title "Generative adversarial network in medical imaging: A review" @default.
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- W2890139949 cites W2100001257 @default.
- W2890139949 cites W2100704456 @default.
- W2890139949 cites W2106439909 @default.
- W2890139949 cites W2113952909 @default.
- W2890139949 cites W2129098176 @default.
- W2890139949 cites W2130125423 @default.
- W2890139949 cites W2133665775 @default.
- W2890139949 cites W2141983208 @default.
- W2890139949 cites W2142514727 @default.
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- W2890139949 cites W2789713147 @default.
- W2890139949 cites W2791621240 @default.
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- W2890139949 doi "https://doi.org/10.1016/j.media.2019.101552" @default.
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