Abstract #0082

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

Carola Fischer^1,2, Jens Wetzl², Tobias Schäffter^1,3,4, and Daniel Giese^2,5

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

Synopsis

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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