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Abstract #1171

Highly undersampled GROG-BPE radial data reconstruction using Compressed Sensing

Yumna Bilal1,2, Ibtisam Aslam1,3, Muhammad Faisal Siddiqui1, and Hammad Omer1
1Medical Image Processing Research Group (MIPRG), Department of Electrical & Computer Engineering, COMSATS University Islamabad, Islamabad, Pakistan, 2Department of Electrical Engineering, University of Gujrat, Gujrat, Pakistan, 3Service of Radiology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland

This work aims at reconstructing the undersampled non-Cartesian k-space signals by generating a cloud of randomly located additional points through GRAPPA Operator Gridding (GROG) facilitated Bunch Phase Encoding (BPE) collectively termed as GROG-BPE scheme. Gridding of this data is performed onto a Cartesian grid. Inherent randomness in the gridded BPE data is exploited using Compressed Sensing (CS) to obtain the solution image at higher acceleration factors and the results are compared with conventional CG-INNG method. Every step in the proposed method (right from BPE generation to reconstruction) is self-calibrating and does not require additional calibration signals.

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