Medical Image Expansion Algorithm Based on Generative Adversarial Networks
Generative adversarial networks have achieved significant results in many fields by virtue of their powerful fitting ability.The paper proposes a generative adversarial network-based image generation method for lung CT images,which combines the feature extraction ability of the self-attentive mechanism and the fitting ability of the generative adversarial network to the data distribution,as well as the specificity processing for the input vector,and the experimental results show that the paper method gen-erates images with high quality as well as usability.
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