期刊
MAGNETIC RESONANCE IMAGING
卷 30, 期 10, 页码 1483-1494出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.mri.2012.04.012
关键词
Dynamic MRI; Real time; Online method; Compressed sensing; Nuclear norm minimization; Rank deficiency
资金
- Natural Sciences and Engineering Research Council of Canada
- Qatar National Research Fund
This work addresses the problem of online reconstruction of dynamic magnetic resonance images (MRI). The proposed method reconstructs the difference between the images of previous and current time frames. This difference image is modeled as a rank deficient matrix and is solved from the partially sampled k-space data via nuclear norm minimization. Our proposed method has been compared against state-of-the-art offline and online reconstruction methods. Our method has similar reconstruction accuracy as the offline method and significantly higher accuracy compared to the online technique. It is about an order of magnitude faster than the online technique compared against. Our experimental data consisted of dynamic MRI data that were collected at 6 to 7 frames per second and having resolutions of 128x128 and 256x256 pixels per frame. Experimental evaluation indicates that our proposed method is capable of reconstructing 128x128 images at the rate of 4 frames per second and 256x256 images at the rate of 2 frames per second. The previous online method requires about 3.75 s for reconstructing each image. The improvement in reconstruction speed is clearly discernible. Moreover, our method has a reconstruction error that is about half that of the previous online method. (C) 2012 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据