Abstract #3441

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

Husnain Javid Bhatti^1,2, Fariha Aamir¹, Ibtisam Aslam^1,3, Khan Afsar^1,4, 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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