Autoencoder-based conditional optimal transport generative adversarial network for medical image generation

Autoencoder-based conditional optimal transport generative adversarial network for medical image generation

Medical image generation has recently garnered significant interest among researchers. However, the primary generative models, such as Generative Adversarial Networks (GANs), often encounter challenges during training, including mode collapse. To address these issues, we proposed the AE-COT-GAN mode...

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Bibliographic Details
Main Authors: Jun Wang, Bohan Lei, Liya Ding, Xiaoyin Xu, Xianfeng Gu, Min Zhang
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Visual Informatics
Subjects:
Medical image generation
Mode collapse
Mode mixing
Optimal transport
Generative adversarial networks
Online Access:http://www.sciencedirect.com/science/article/pii/S2468502X23000529

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http://www.sciencedirect.com/science/article/pii/S2468502X23000529

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