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Abstract #0601

A Novel Image Reconstruction Algorithm for Radial MRI Data Acquired with a Rotating Radio-frequency Coil (RRFC)

Andrew Phair1, Michael Brideson1, Jin Jin2,3,4, Mingyan Li2, Stuart Crozier2, and Lawrence Forbes1
1School of Natural Sciences, University of Tasmania, Hobart, Australia, 2School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia, 3ARC Training Centre for Innovation in Biomedial Imaging Technology, University of Queensland, Brisbane, Australia, 4Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States

We present WARF, a novel reconstruction algorithm for radial MRI data acquired with a rotating radio-frequency coil (RRFC). The algorithm reconstructs each pixel as a weighted sum of all acquired data, with the weights determined by the k-space sampling pattern. The theory behind WARF leading to the derivation of appropriate weights is presented, and then WARF is applied to both simulated and experimental data sets. The results indicate WARF is achieving an improved robustness to RRFC angular velocity variability and k-space trajectory deviation compared with existing reconstruction methods.

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