Big Data Research ›› 2020, Vol. 6 ›› Issue (5): 45-54.doi: 10.11959/j.issn.2096-0271.2020043

• TOPIC:MEDICAL BIG DATA • Previous Articles     Next Articles

Study on domain adaptation of medical data based on generative adversarial network

Hufei YU,Jingxi WEN,Jiang XIN,Yan TANG   

  1. School of Computer Science Engineering,Central South University,Changsha 410083,China
  • Online:2020-09-20 Published:2020-09-29

Abstract:

In the study of medical imaging aided diagnosis,researchers often collect a lot of training data coming from different hospitals (named variety fields).But because of the certain field has insufficient training data,the deep learning model would get very poor performance on the test data of this field.To mitigate this problem,a method to study domain adaptation of the difference between male and female brain images based on the generative adversarial network was proposed.The data distribution of different domains was learned and the key features were extracted by using the generative adversarial network,and then the differences between male and female brain images in different domains were studied based on the extracted key features.Experiments show that the method can also achieve more than 80% recognition accuracy in the domain with only a small amount of data involved in training.

Key words: deep learning, generative adversarial network, domain adaptation, medical image

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