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
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
Compressed
Sensing reconstruction for radially undersampled GROG-BPE data with random
blipping yields images with better clarity and quantifying parameters than conventionally
used GROG-BPE CG-INNG method at higher acceleration factors.
Figure 1:
Block diagram of the proposed CS-GROG-BPE scheme. Undersampled radial signal is
used to generate the Bunch Phase Encoded k-space at the specified k_max and
NBP, using GROG. Non-Cartesian BPE k-space is gridded to Cartesian k-space
using a defined oversampling factor and step-size using GROG. Gridded k-space
is then reconstructed coil-by-coil by CS algorithm with specified
regularization parameters. Coil-by-coil reconstructed images are then combined
using sum-of-square reconstruction to yield the final output image.
Figure 2: Reconstruction Results (a) shows fully sampled
ground truth image. (b) shows results of CS-GROG-BPE method proposed in this
work, at acceleration at AF = 8, 10, 12. (c) shows results of GROG-BPE CG-INNG method2
with the same BPE generation and gridding parameters. Quantifying parameters
including AF, RMSE and SNR have been provided underneath each reconstructed
image.
