Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
Med Image Anal. 2014 Aug;18(6):857-65. doi: 10.1016/j.media.2014.04.010. Epub 2014 May 5.
In this paper, we propose a Compressive Sensing based approach to the problem of real-time reconstruction of MR image sequences. Our proposed method is able to extract useful priori information and incorporate it into a modified iterative thresholding algorithm for fast casual reconstruction of MR images from highly undersampled k-space data. Through extensive experimental results we show that our proposed method achieves superior reconstruction quality, while having a lower computational complexity and memory requirements compared to the other state-of-the-art methods.
在本文中，我们提出了一种基于压缩感知的方法来解决磁共振图像序列的实时重建问题。我们的方法能够提取有用的先验信息，并将其纳入到一个改进的迭代阈值算法中，从而从高度欠采样的 k 空间数据中快速重建磁共振图像。通过广泛的实验结果，我们表明，与其他最先进的方法相比，我们的方法具有更高的重建质量，同时具有更低的计算复杂度和内存需求。
