Automated subject-specific pixels selection for improved image reconstruction in free-running coronary MRA using SIMBA
Ludovica Romanin1,2, Christopher W. Roy2, Milan Prsa3, Tobias Rutz4, Estelle Tenisch2, Matthias Stuber2,5, and Davide Piccini1,2
1Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 2Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, 3Division of Pediatric Cardiology, Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, 4Service of Cardiology, Heart and Vessel Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, 5Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
This work proposes an automated subject-specific individual pixels selection as an alternative to a fixed coil selection for the initialization of the input data to a similarity-driven multi-dimensional binning algorithm (SIMBA) for free-running motion-suppressed whole-heart acquisitions. By selecting timeseries with a high low-frequency energy content, we include only pixels with respiratory and cardiac information. Compared to the original method, this leads to a more accurate choice of end-expiration and diastolic phases for the reconstruction of sharp whole-heart and coronary images. Moving forward, the method needs to be refined, optimized and tested to further improve the image quality.
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