Diagnostic accuracy of 3D deep-learning-based fully automated estimation of patient-level minimum fractional flow reserve from coronary computed tomography angiography-Reference-Cited by-同舟云学术

Diagnostic accuracy of 3D deep-learning-based fully automated estimation of patient-level minimum fractional flow reserve from coronary computed tomography angiography

Published:2019-06-23 Issue: Volume: Page:
ISSN:2047-2404
Container-title:European Heart Journal - Cardiovascular Imaging
language:en
Short-container-title:

Author:

Kumamaru Kanako K¹^ORCID,Fujimoto Shinichiro²,Otsuka Yujiro¹³,Kawasaki Tomohiro⁴,Kawaguchi Yuko²,Kato Etsuro²,Takamura Kazuhisa²,Aoshima Chihiro²,Kamo Yuki²,Kogure Yosuke⁵,Inage Hidekazu⁵,Daida Hiroyuki²,Aoki Shigeki¹

Affiliation:

1. Department of Radiology, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, Japan

2. Department of Cardiovascular Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, Japan

3. Milliman, Inc., Urbannet Kojimachi Bldg. 8F, 1-6-2 Kojimachi, Chiyoda-ku, Tokyo, Japan

4. Department of Cardiology, Cardiovascular Center, Shin-Koga Hospital, 2-1-1 Hongo, Bunkyo-ku, Tokyo, Japan

5. Department of Radiological Technology, Juntendo University Hospital, 2-1-1 Hongo, Bunkyo-ku, Tokyo, Japan

Funder

Japan Agency for Medical Research and Development

Publisher

Oxford University Press (OUP)

Subject

Cardiology and Cardiovascular Medicine,Radiology Nuclear Medicine and imaging,General Medicine

Link

http://academic.oup.com/ehjcimaging/advance-article-pdf/doi/10.1093/ehjci/jez160/28856291/jez160.pdf

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4. Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis;Taylor;J Am Coll Cardiol,2013

5. Experience with an on-site coronary computed tomography-derived fractional flow reserve algorithm for the assessment of intermediate coronary stenoses;Donnelly;Am J Cardiol,2018

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