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Abstract #3441

Calibration-less pMRI for the Reconstruction of Radially Encoded data using GROG based CS

Husnain Javid Bhatti1,2, Fariha Aamir1, Ibtisam Aslam1,3, Khan Afsar1,4, and Hammad Omer1
1Department of Electrical and Computer Engineering, COMSATS University Islamabad (CUI), Islamabad, Pakistan, 2School of Electrical Engineering and Computers Science, National University of Science and Technology (NUST), Islamabad, Pakistan, 3Department of Radiology and Medical Informatics, Hospital University of Geneva, GENEVA, Switzerland, 4Department of Electronic science and Technology, Xiamen University, Xiamen, China

To reduce MRI scan time, under-sampled non-Cartesian trajectories are used which lead to artifacts. This work proposes a new method ‘GROG with calibration-less pMRI for CS based p-thresholding’ to reconstruct MR images from the under-sampled radial k-space data. The proposed method is validated on the phantom and 1.5T human head data and provides significant improvement both visually and in terms of quantifying parameters (AP, RMSE & PSNR) e.g. 77% and 86% improvement in AP, 5% and 32% improvement in RMSE, 7% and 11% improvement in PSNR at AF=4 for the phantom data than POCS and pseudo Cartesian GRAPPA, respectively.

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