Automated quantification of epicardial adipose tissue from non-contrast CT on multi-center and multi-vendor data using deep learning

Commandeur F, Göller M, Razipour A, Cadet S, Hell M, Kwiecinski J, Chen X, Chang HJ, Achenbach S, Berman DS, Slomka PJ, Tamarappoo BK, Dey D, Marwan M (2019)

Publication Type: Conference contribution

Publication year: 2019

Journal

European Heart Journal Oxford University Press

Publisher: OXFORD UNIV PRESS

City/Town: OXFORD

Pages Range: 3645-3645

Conference Proceedings Title: EUROPEAN HEART JOURNAL

Event location: Paris FR

DOI: 10.1093/eurheartj/ehz746.0104

Authors with CRIS profile

Markus Göller Department of Medicine 2 – Cardiology and Angiology Stephan Achenbach Lehrstuhl für Innere Medizin II Mohamed Marwan Department of Medicine 2 – Cardiology and Angiology

Involved external institutions

Cedars-Sinai Medical Center US United States (USA) (US) Yonsei University KR Korea, Republic of (KR)

How to cite

APA:

Commandeur, F., Göller, M., Razipour, A., Cadet, S., Hell, M., Kwiecinski, J.,... Marwan, M. (2019). Automated quantification of epicardial adipose tissue from non-contrast CT on multi-center and multi-vendor data using deep learning. In EUROPEAN HEART JOURNAL (pp. 3645-3645). Paris, FR: OXFORD: OXFORD UNIV PRESS.

MLA:

Commandeur, F., et al. "Automated quantification of epicardial adipose tissue from non-contrast CT on multi-center and multi-vendor data using deep learning." Proceedings of the ESC Congress / World Congress of Cardiology, Paris OXFORD: OXFORD UNIV PRESS, 2019. 3645-3645.

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