Abstract #0601

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

Andrew Phair¹, Michael Brideson¹, Jin Jin^2,3,4, 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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