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Abstract #0633

Automated Heartbeat Detection for Self-Gated Fetal Cardiac MRI

Robin Demesmaeker1, Tobias Kober1,2,3, Jérôme Yerly3,4, Jérôme Chaptinel3, Milan Prsa5, Yvan Mivelaz5, Leonor Alamo3, Yvan Vial6, Gregoire Berchier3, Chantal Rohner3, Matthias Stuber3,4, and Davide Piccini1,2,3

1Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 2LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 3Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 4Center for Biomedical Imaging (CIBM), Lausanne, Switzerland, 5Department of Pediatrics, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, 6Department of Gynecology-Obstetrics, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland

Fetal cardiac cine MRI requires an MRI-based cardiac gating signal since recording a fetal ECG is fraught with significant challenges. Existing approaches usually extract the signal from real-time image series and mandate semi-manual user interaction. However, these give often inconsistent results or suffer from reduced spatio-temporal resolution. We propose a novel algorithm which automatically localizes the fetal heart on real-time low-resolution images, and provides a precise frequency estimate of the cardiac motion signal that can be used for gating. We show that this automated method leads to images with equal or better quality than those obtained with the manual approach.

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