东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2011, Vol. 32 ›› Issue (8): 1101-1104+1110.DOI: -

• 论著 • 上一篇    下一篇

一种改进的磁共振并行成像k空间数据采集算法

吴春俐;胡文娟;阚如文;于健;   

  1. 东北大学信息科学与工程学院;吉林大学通信工程学院;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家高技术研究发展计划项目(2007AA03Z237)

An improved algorithm of k-space data acquisition for parallel MRI

Wu, Chun-Li (1); Hu, Wen-Juan (1); Kan, Ru-Wen (2); Yu, Jian (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China; (2) School of Communication Engineering, Jilin University, Changchun 130025, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Wu, C.-L.
  • About author:-
  • Supported by:
    -

RichHTML

1

PDF (PC)

1308

摘要： 为进一步缩短磁共振成像时间,改善图像质量,提出了一种改进的有限脉冲响应(FIR)GRAPPA算法.与传统的权重固定的FIR GRAPPA算法模型相比,该算法考虑了相位方向的变化,包含更多的k空间数据且更符合并行成像数据拟合的物理过程.为验证该算法的有效性,对人体心脏和大脑图像的原始数据分别进行仿真实验,得到了在较大加速因子下的重建图像及均方误差.与传统的GRAPPA算法及其他改进的GRAPPA算法进行比较,结果发现,利用改进算法重建的图像更清晰,均方误差更小.因此,本文提出的改进GRAPPA算法有效可行.

关键词: 磁共振, 并行成像, k空间数据, 广义自动校准部分并行采集(GRAPPA), 加速因子

Abstract: To further reduce the imaging time and improve the image quality, an improved GRAPPA algorithm of finite impulse response (FIR) is presented. Compared with the conventional GRAPPA algorithms with fixed weights, the proposed algorithm considers the phase change of the weighted coefficients, has a better description for the correlation of k-space data, and is more consistent with the physical process of data fitting for parallel imaging. To demonstrate the validity of the improved algorithm, the simulation experiments were performed with the original data of brain and cardiac images. The reconstructed images and the mean square error (MSE) were obtained with a higher acceleration factor, and were compared with the conventional and other GRAPPA algorithms. The results show that the reconstructed images are clearer and the MSE value are much smaller using the proposed algorithm. Therefore, the improved k-space data acquisition algorithm is effective and feasible.

中图分类号: