Improved Multi-Head Self-Attention Classification Network for Multi-View Fetal Echocardiography Recognition-Reference-Cited by-同舟云学术

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Improved Multi-Head Self-Attention Classification Network for Multi-View Fetal Echocardiography Recognition

Published:2023-07-24 Issue: Volume: Page:
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Container-title:2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Zhang Yingying¹,Zhu Haogang²,Wang Yan²,Wang Jingyi³,He Yihua³

Affiliation:

1. Beihang University,School of Biological Science and Medical Engineering,Beijing,China,100191

2. Beihang University,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine,Beijing,China,100191

3. Capital Medical University,Echocardiography Medical Center Beijing Anzhen Hospital,Beijing,China,100029

Funder

Research and Development

National Natural Science Foundation of China

Beijing Municipal Administration of Hospitals

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10339936/10339939/10340120.pdf?arnumber=10340120

Reference14 articles.

1. Fetal echocardiography for early detection of congenital heart diseases

2. The importance of quality management in fetal measurement

3. ISUOG Practice Guidelines (updated): sonographic screening examination of the fetal heart

4. Consensus on the medical model and technical process of multidisciplinary diagnosis and treatment and precision integrated prevention and management of foetal heart disease in maternal-foetal medicine (Part II): Consensus on detailed risk stratification diagnosis technology of foetal echocardiography;Chin. J. Perinatal Med.,2022

5. Detection of fetal cardiac anomalies: cost‐effectiveness of increased number of cardiac views

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