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Abstract #0082

Automatic background phase correction on 4D Flow using M-estimate SAmple Consensus (MSAC)

Carola Fischer1,2, Jens Wetzl2, Tobias Schäffter1,3,4, and Daniel Giese2,5
1Department of Medical Imaging, Technical University of Berlin, Berlin, Germany, 2Magnetic Resonance, Siemens Healthcare GmbH, Erlangen, Germany, 3Physikalisch-Technische-Bundesanstalt (PTB), Braunschweig and Berlin, Germany, 4School of Imaging Sciences and Biomedical Engineering, King's College London, London, SE1 7EH, United Kingdom, 5Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany


4D Flow data requires background phase removal to correctly quantify flow velocities. Typical methods are semi-automatic, requiring manual parameter input and remain time-consuming. Furthermore, correction methods based on stationary tissue segmentation fail when in the presence of wrap-around artifacts. In contrast, the proposed M-Estimate SAmple Consensus (MSAC) algorithm robustly and fully automatically corrects background phases by rejecting pixels that show large deviations from the most probable phase offset fit. A parameter sensitivity analysis is proposed following in vivo application in 13 datasets.

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