A Pseudo-Siamese Feature Fusion Generative Adversarial Network for Synthesizing High-Quality Fetal Four-Chamber Views-Reference-Cited by-同舟云学术

A Pseudo-Siamese Feature Fusion Generative Adversarial Network for Synthesizing High-Quality Fetal Four-Chamber Views

Author:

Qiao Sibo¹^ORCID,Pan Silin²^ORCID,Luo Gang²^ORCID,Pang Shanchen¹^ORCID,Chen Taotao³,Singh Amit Kumar⁴^ORCID,Lv Zhihan⁵^ORCID

Affiliation:

1. School of Computer Science and Technology, University of Petroleum, Qingdao, Shandong, China

2. Heart Center, Women and Children’s Hospital, Qingdao, Shandong, China

3. Department of Ultrasound, Women and Children’s Hospital, Qingdao, Shandong, China

4. Department of Computer Science and Engineering, National Institute of Technology, Patna, India

5. Department of Game Design, Faculty of Arts, Uppsala University, Uppsala, Sweden

Funder

National Natural Science Foundation of China

Major Science and Technology Innovation Project of Shandong Province

Tai Shan Industry Leading Talent Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

Reference47 articles.

2. Conditional image synthesis with auxiliary classifier GANs;odena;Proc Int Conf Mach Learn,0

4. Generative adversarial text to image synthesis;reed;Proc Int Conf Mach Learn,0

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