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Concerns in the use of adversarial learning for image synthesis in cardiovascular intervention.

作者信息

Higaki Akinori, Miyoshi Toru, Yamaguchi Osamu

机构信息

Department of Cardiology, Ehime Prefectural Central Hospital, 83 Kasuga-machi, 790-0024 Matsuyama, Ehime, Japan.

Department of Cardiology, Pulmonology, Hypertension and Nephrology, Ehime University Graduate School of Medicine, 454 Shitsukawa, 791-0295 Toon, Ehime, Japan.

出版信息

Eur Heart J Digit Health. 2021 Jul 15;2(4):556. doi: 10.1093/ehjdh/ztab064. eCollection 2021 Dec.

DOI:10.1093/ehjdh/ztab064
PMID:36713093
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9707988/
Abstract
摘要

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Reconstruction of Apical 2-Chamber View From Apical 4- and Long-Axis Views on Echocardiogram Using Machine Learning　- Pilot Study With Deep Generative Modeling.使用机器学习从超声心动图的心尖四腔心视图和长轴视图重建心尖两腔心视图——深度生成建模的初步研究
Circ Rep. 2019 Mar 20;1(4):197. doi: 10.1253/circrep.CR-19-0011.
3
Automated interpretation of the coronary angioscopy with deep convolutional neural networks.利用深度卷积神经网络对冠状动脉血管镜检查进行自动解读。
Open Heart. 2020 May;7(1). doi: 10.1136/openhrt-2019-001177.
4
Generative adversarial network in medical imaging: A review.生成对抗网络在医学影像中的应用：综述
Med Image Anal. 2019 Dec;58:101552. doi: 10.1016/j.media.2019.101552. Epub 2019 Aug 31.
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Visual Turing test for computer vision systems.计算机视觉系统的视觉图灵测试。
Proc Natl Acad Sci U S A. 2015 Mar 24;112(12):3618-23. doi: 10.1073/pnas.1422953112. Epub 2015 Mar 9.