Li Shuo, Zhu Yanchun, Xie Yaoqin, Gao Song
Department of Biophysics, School of Basic Medical Sciences, Peking University, Beijing, China.
Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
PLoS One. 2018 Jan 30;13(1):e0191569. doi: 10.1371/journal.pone.0191569. eCollection 2018.
Dynamic magnetic resonance imaging (DMRI) is used to noninvasively trace the movements of organs and the process of drug delivery. The results can provide quantitative or semiquantitative pathology-related parameters, thus giving DMRI great potential for clinical applications. However, conventional DMRI techniques suffer from low temporal resolution and long scan time owing to the limitations of the k-space sampling scheme and image reconstruction algorithm. In this paper, we propose a novel DMRI sampling scheme based on a golden-ratio Cartesian trajectory in combination with a compressed sensing reconstruction algorithm. The results of two simulation experiments, designed according to the two major DMRI techniques, showed that the proposed method can improve the temporal resolution and shorten the scan time and provide high-quality reconstructed images.
动态磁共振成像（DMRI）用于无创追踪器官运动和药物递送过程。其结果可提供与病理学相关的定量或半定量参数，从而使DMRI在临床应用中具有巨大潜力。然而，由于k空间采样方案和图像重建算法的限制，传统的DMRI技术存在时间分辨率低和扫描时间长的问题。在本文中，我们提出了一种基于黄金分割笛卡尔轨迹并结合压缩感知重建算法的新型DMRI采样方案。根据两种主要的DMRI技术设计的两个模拟实验结果表明，该方法可以提高时间分辨率，缩短扫描时间，并提供高质量的重建图像。
