Improved compressed sensing MRI with multi-channel data using reweighted l(1) minimization

Ching-Hua Chang; Jim Ji

doi:10.1109/IEMBS.2010.5627890

Improved compressed sensing MRI with multi-channel data using reweighted l(1) minimization

Annu Int Conf IEEE Eng Med Biol Soc. 2010:2010:875-8. doi: 10.1109/IEMBS.2010.5627890.

Authors

Ching-Hua Chang¹, Jim Ji

Affiliation

¹ Department of Electrical and Computer Engineering, Texas A&M University, TX 77843-3128, USA.

PMID: 21097199
DOI: 10.1109/IEMBS.2010.5627890

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 l(1) minimization to the CS MRI with multi-channel data. The simulated experimental results show that the new method can provide improved reconstruction quality.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Algorithms*
Data Compression / methods*
Image Enhancement / methods*
Image Interpretation, Computer-Assisted / methods*
Magnetic Resonance Imaging / methods*
Reproducibility of Results
Sensitivity and Specificity