Improving multi-channel compressed sensing MRI with reweighted l 1 minimization. Academic Article

abstract

• Integrating compressed sensing (CS) and parallel imaging (PI) with multi-channel receiver has proven to be an effective technology to speed up magnetic resonance imaging (MRI). In this paper, we propose a method that extends the reweighted l 1 minimization to the CS-MRI with multi-channel data. The method applies a reweighted l 1 minimization algorithm to reconstruct each channel image, and then generates the final image by a sum-of-squares method. Computer simulations based on synthetic data and in vivo MRI imaging data show that the new method can improve the reconstruction quality at a slightly increased computation cost.

authors

• Ji, Jim

published proceedings

• Quant Imaging Med Surg

author list (cited authors)

• Chang, C., & Ji, J. X.

citation count

• 5

complete list of authors

• Chang, Ching-Hua||Ji, Jim X

publication date

• February 2014

published in

• Quantitive Imaging in Medicine and Surgery  Journal

keywords

• Compressed Sensing Mri
• Image Reconstruction
• Multi-channel Receive Arrays
• Reweighted L1 Minimization

PubMed Central ID

• 24649431

Digital Object Identifier (DOI)

• 10.3978/j.issn.2223-4292.2014.03.02

start page

• 19

end page

• 23

volume

• 4

issue

• 1