DocumentCode
1771786
Title
Accelerated dynamic MRI via inter-frame motion estimation
Author
Chuqing Cao ; Ying Sun
Author_Institution
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
fYear
2014
fDate
April 29 2014-May 2 2014
Firstpage
449
Lastpage
452
Abstract
The sparsity of MR images has been utilized to significantly undersample k-space measurements for accelerated MRI. In dynamic MRI, besides the spatiotemporal structures of images, the motion information should be considered to improve the reconstruction performance. Motivated by this, we propose a new method to recover dynamic MR images using partial k-space data based on the estimation of inter-frame motion. Our method consists of three main steps: single frame reconstruction, inter-frame motion estimation, and image sequence recovery. In contrast to algorithms which use a single reference frame for motion estimation, the motion information of each image in a dynamic MRI sequence is estimated according to adjacent frames. Since motion is estimated from the reconstructed images, the recovery process is robust against both noise and artifacts. The proposed method was evaluated on two dynamic MRI datasets, and compared with several state-of-the-art reconstruction methods. Experimental results demonstrate the effectiveness and robustness of the proposed method.
Keywords
biomedical MRI; compressed sensing; image reconstruction; image sequences; medical image processing; motion estimation; MR image sparsity; accelerated dynamic MRI; artifacts; dynamic MR images; dynamic MRI datasets; dynamic MRI sequence; image sequence recovery; interframe motion estimation; motion information; noise; partial k-space data; reconstructed images; reconstruction performance; recovery process; single frame reconstruction; single reference frame; spatiotemporal structures; undersample k-space measurements; Coils; Compressed sensing; Dynamics; Image reconstruction; Magnetic resonance imaging; Motion estimation; Compressed sensing; inter-frame motion; motion estimation; sparse representation;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on
Conference_Location
Beijing
Type
conf
DOI
10.1109/ISBI.2014.6867905
Filename
6867905
Link To Document