Title :
Improved compressed sensing MRI with multi-channel data using reweighted l1 minimization
Author :
Chang, Ching-Hua ; Ji, Jim
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
fDate :
Aug. 31 2010-Sept. 4 2010
Abstract :
Compressed sensing (CS) is an emerging technology to speed up magnetic resonance imaging (MRI). Since most clinical MRI scanners are equipped with multi-channel receiver systems, there has been a number of works to integrate CS with multi-channel systems. In this paper, we propose a method that extends the reweighted l1 minimization to the CS MRI with multi-channel data. The simulated experimental results show that the new method can provide improved reconstruction quality.
Keywords :
biomedical MRI; data compression; image coding; image reconstruction; medical image processing; MRI; compressed sensing; magnetic resonance imaging; multichannel receiver systems; reconstruction; reweighted minimization; Acceleration; Arrays; Compressed sensing; Image reconstruction; Magnetic resonance imaging; Minimization; Compressed Sensing; Image Reconstruction; Multi-channel Phased Array; Reweighted l1 Minimization; Algorithms; Data Compression; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Reproducibility of Results; Sensitivity and Specificity;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5627890
