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Abstract #2206

Automatic Detection of Arrhythmia in ECG-free Real-time MRI

Anja Hennemuth1,2, Christina Unterberg3, Sebastian Ulrich Kelle4, Martin Uecker3, Jens Frahm5, and Markus Hüllebrand1,2
1Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany, 2Fraunhofer MEVIS, Bremen, Germany, 3Universitätsmedizin Göttingen, Göttingen, Germany, 4Deutsches Herzzentrum Berlin, Berlin, Germany, 5Max-Planck-Institut fuer biophysikalische Chemie, Göttingen, Germany

The analysis of cardiac function in patients suffering from arrhythmia poses a problem for conventional ECG-synchronized imaging and the patients' ability to hold their breath. Real-time imaging approaches provide ungated image data, which contains the information about the motion variation induced by breathing and arrhythmia but require a high effort in post-processing and interpretation. The goal of the presented work is to enable an automatic analysis of cardiac real-time image sequences of patients suffering from arrhythmia. To this end, we combine a fast CNN-based segmentation of the myocardium with a curve pattern analysis of the blood volume changes over time.

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