K-T ISD: Compressed sensing with iterative support detection for dynamic MRI

Author

Liang, Dong ; DiBella, Edward V R ; Chen, Rong-Rong ; Ying, Leslie

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Univ. of Wisconsin-Milwaukee, Milwaukee, WI, USA

fYear

2011

fDate

March 30 2011-April 2 2011

Firstpage

1264

Lastpage

1267

Abstract

In this paper, we propose a new k-t Iterative Support Detection (k-t ISD) method to improve the CS reconstruction for dynamic cardiac MRI by incorporating additional information on the support of the dynamic image in x-f space. The proposed method uses an iterative procedure for alternating image reconstruction and support detection in x-f space. Experimental results demonstrate that the proposed k-t ISD method improves the reconstruction quality of dynamic cardiac MRI over the basic CS method in which support information is not exploited.

Keywords

biomedical MRI; cardiology; image reconstruction; iterative methods; medical image processing; CS reconstruction; K-T ISD; compressed sensing; dynamic cardiac MRI; image reconstruction; iterative support detection; Compressed sensing; Encoding; Fourier transforms; Image reconstruction; Magnetic resonance imaging; Matching pursuit algorithms; Minimization; Compressed sensing; dynamic MRI; k−t Iterative Support Detection (k−t ISD); partially known support; truncated ℓ1 minimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on

Conference_Location

Chicago, IL

ISSN

1945-7928

Print_ISBN

978-1-4244-4127-3

Electronic_ISBN

1945-7928

Type

conf

DOI

10.1109/ISBI.2011.5872631

Filename

5872631