生物医学工程学杂志

生物医学工程学杂志

生成式对抗网络在医学图像处理中的应用

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近年来,研究人员将众多领域方法引入到医学图像处理中。经过不断改进,医学图像处理算法的效果和效率均得到不同程度的提高。目前,生成式对抗网络(GAN)在医学图像处理领域中的应用研究发展迅速。本文主要综述了 GAN 在医学图像处理中的应用研究情况,介绍了 GAN 的基本概念,并从医学图像降噪、医学图像检测、医学图像分割、医学图像合成、医学图像重建和医学图像分类等六个方面对 GAN 应用研究的最新进展进行了归纳总结,最后对该领域中值得进一步研究的方向进行了展望。

In recent years, researchers have introduced various methods in many domains into medical image processing so that its effectiveness and efficiency can be improved to some extent. The applications of generative adversarial networks (GAN) in medical image processing are evolving very fast. In this paper, the current status in this area has been reviewed. Firstly, the basic concepts of the GAN were introduced. And then, from the perspectives of the medical image denoising, detection, segmentation, synthesis, reconstruction and classification, the applications of the GAN were summarized. Finally, prospects of further research in this area were presented.

关键词: 生成式对抗网络; 医学图像; 深度学习

Key words: generative adversarial networks; medical images; deep learning

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