  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.
