Fully automatic AI-based valve motion parameter extraction on long axis CINE images – application on N=11000 patient datasets

Yoon SS, Fischer C, Toupin S, Pezel T, Garot J, Wetzl J, Maier A, Giese D (2022)

Publication Type: Conference contribution, Abstract of lecture

Publication year: 2022

Event location: London GB

DOI: 10.1093/ehjci/jeac141.020

Authors with CRIS profile

Seung Su Yoon Lehrstuhl für Informatik 5 (Mustererkennung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung) Daniel Giese

Involved external institutions

Institut Cardiovasculaire Paris Sud (ICPS) FR France (FR) Technische Universität Berlin DE Germany (DE) Siemens AG, Healthcare Sector DE Germany (DE)

How to cite

APA:

Yoon, S.S., Fischer, C., Toupin, S., Pezel, T., Garot, J., Wetzl, J.,... Giese, D. (2022). Fully automatic AI-based valve motion parameter extraction on long axis CINE images – application on N=11000 patient datasets. Paper presentation at Artificial Intelligence in Cardiovascular Magnetic Resonance Imaging - A Joint Summit of the EACVI and SCMR, London, GB.

MLA:

Yoon, Seung Su, et al. "Fully automatic AI-based valve motion parameter extraction on long axis CINE images – application on N=11000 patient datasets." Presented at Artificial Intelligence in Cardiovascular Magnetic Resonance Imaging - A Joint Summit of the EACVI and SCMR, London 2022.

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