MSGAN: Multi-Stage Generative Adversarial Networks for Cross-Modality Domain Adaptation-Reference-Cited by-同舟云学术

MSGAN: Multi-Stage Generative Adversarial Networks for Cross-Modality Domain Adaptation

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Wang Yan¹,Chen Yixin²,Wang Wenjun³,Zhu Haogang⁴

Affiliation:

1. School of Instrumentation and Optoelectronic Engineering, Beihang University,Beijing,China,100191

2. BioMind Technology, Zhongguancun Medical Engineering Center,Beijing,China,100872

3. Medical big Data Center, Chinese PLA, General Hospital,Beijing,P.R. China,100853

4. Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University,State Key Laboratory of Software Development Enviroment,Beijing,China,100191

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871048.pdf?arnumber=9871048

Reference23 articles.

1. Simultaneous Segmentation of Four Cardiac Chambers in Fetal Echocardiography

2. Generative adversarial nets;goodfellow;Advances in neural information processing systems,0

3. Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks

4. Adversarial domain adaptation to improve automatic breast cancer grading in lymph nodes

5. Densely Connected Convolutional Networks

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