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arXiv 1907.13033eess.IVcs.CV

Lung image segmentation by generative adversarial networks

School of Applied Mathematics, Xiamen University of Technology(厦门理工学院应用数学学院)

Jiaxin Cai, Hongfeng Zhu

英文摘要:

Lung image segmentation plays an important role in computer-aid pulmonary diseases diagnosis and treatment. This paper proposed a lung image segmentation method by generative adversarial networks. We employed a variety of generative adversarial networks and use its capability of image translation to perform image segmentation. The generative adversarial networks was employed to translate the original lung image to the segmented image. The generative adversarial networks based segmentation method was test on real lung image data set. Experimental results shows that the proposed method is effective and outperform state-of-the art method.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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