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Abstract #2303

A local SAR compression algorithm with improved compression, speed and flexibility

Stephan Orzada1, Thomas M. Fiedler1, Harald H. Quick2,3, and Mark E. Ladd1,2,4,5
1Medical Physics in Radiology (E020), German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Erwin L. Hahn Institute for MRI, University Duisburg-Essen, Essen, Germany, 3High-Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany, 4Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany, 5Faculty of Medicine, University of Heidelberg, Heidelberg, Germany

For parallel transmit systems, control of local SAR is very important to ensure safety. For pulse calculation and online supervision, compression of the SAR matrices is used to reduce calculation effort. The original clustering method by Eichfelder et al. was later outperformed by a method proposed by Lee et al. We propose an enhancement to Lee’s algorithm that further increases compression efficiency, speed and flexibility by iteratively reducing the overestimation.

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