Title :
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
fDate :
March 30 2011-April 2 2011
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;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-4127-3
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2011.5872631