Corpus ID: 229547264

Generator Versus Segmentor: Pseudo-healthy Synthesis

@article{Yunlong2020GeneratorVS,
  title={Generator Versus Segmentor: Pseudo-healthy Synthesis},
  author={Zhang Yunlong and Lin ChenXin and Lin Xin and Sun Liyan and Zhu Yihong and Huang Yue and Ding Xinghao and Liu Xiaoqing and Yu Yizhou},
  journal={arXiv: Computer Vision and Pattern Recognition},
  year={2020}
}
Pseudo-healthy synthesis is defined as synthesizing a subject-specific 'healthy' image from a pathological one, with applications ranging from segmentation to anomaly detection. In recent years, the existing GAN-based methods proposed for pseudo-healthy synthesis aim to eliminate the global differences between synthetic and healthy images. In this paper, we discuss the problems of these approaches, which are the style transfer and artifacts respectively. To address these problems, we consider… Expand

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