Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada.
Magn Reson Imaging. 2012 Dec;30(10):1483-94. doi: 10.1016/j.mri.2012.04.012. Epub 2012 Jul 11.
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 128×128 and 256×256 pixels per frame. Experimental evaluation indicates that our proposed method is capable of reconstructing 128×128 images at the rate of 4 frames per second and 256×256 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.
这项工作解决了动态磁共振成像（MRI）在线重建的问题。所提出的方法重建了前一帧和当前帧之间的图像差异。该差分图像被建模为秩亏矩阵，并通过核范数最小化从部分采样的 k 空间数据中求解。我们提出的方法与最新的离线和在线重建方法进行了比较。我们的方法与离线方法具有相似的重建精度，并且与在线技术相比具有显著更高的精度。与在线技术相比，它的速度快一个数量级。我们的实验数据由每秒采集 6 到 7 帧的动态 MRI 数据组成，每帧的分辨率为 128×128 和 256×256 像素。实验评估表明，我们提出的方法能够以每秒 4 帧的速度重建 128×128 图像，以每秒 2 帧的速度重建 256×256 图像。之前的在线方法需要大约 3.75 秒来重建每个图像。重建速度的提高是显而易见的。此外，我们的方法的重建误差大约是之前在线方法的一半。
