Fast Reconstruction for Sparse MR Images in Compressed Sensing

Author

Yonggui Zhu ; Xiaoman Liu

Author_Institution

Sch. of Sci., Commun. Univ. of China, Beijing, China

fYear

2013

fDate

26-28 July 2013

Firstpage

9

Lastpage

13

Abstract

In this paper, we apply TV sparsifying MR image reconstruction method proposed in [ Y. G. Zhu and X. L. Yang, Journal of Signal and Information Processing, 2 (2011), pp. 44-51] to compressed sensing MRI model with wavelet sparsity. The fast method to reconstruct MR images with wavelet sparsity in compressed sensing is presented. This approach can exactly reconstruct the MR image from the partial Fourier data. The convergence of the fast method is analyzed. Some MR images are employed to test in the numerical experiments, and the results demonstrate that this method is very efficient in the reconstruction of MR images.

Keywords

Fourier transforms; biomedical MRI; compressed sensing; image reconstruction; medical image processing; wavelet transforms; TV; compressed sensing; numerical experiments; partial Fourier data; sparse MR image reconstruction; wavelet sparsity; Compressed sensing; Convergence; Educational institutions; Image reconstruction; Magnetic resonance imaging; Phantoms; Signal to noise ratio; Compressed Sensing; Image Reconstruction; Magnetic Resonance Image; Wavelet Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Graphics (ICIG), 2013 Seventh International Conference on

Conference_Location

Qingdao

Type

conf

DOI

10.1109/ICIG.2013.8

Filename

6643627