东北大学学报:自然科学版 ›› 2017, Vol. 38 ›› Issue (7): 936-940.DOI: 10.12068/j.issn.1005-3026.2017.07.006

• 信息与控制 • 上一篇    下一篇

基于梯度下降法的双能CT双物质分解算法

滕月阳, 郑孙易, 卢子鹏, 康雁   

  1. (东北大学 中荷生物医学与信息工程学院, 辽宁 沈阳110169)
  • 收稿日期:2016-06-30 修回日期:2016-06-30 出版日期:2017-07-15 发布日期:2017-07-07
  • 通讯作者: 滕月阳
  • 作者简介:滕月阳(1979-),男,辽宁沈阳人,东北大学讲师,博士; 康雁(1964-),男,辽宁沈阳人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(61372014,61302013); 辽宁省科技厅工业攻关及成果产业化项目(2014305001).

Two-Material Decomposition Algorithm of Dual-Energy CT Based on Gradient Descent Method

TENG Yue-yang, ZHENG Sun-yi, LU Zi-peng, KANG Yan   

  1. School of Sino-Dutch Biomedical and Information Engineering, Northeastern University, Shenyang 110169, China.
  • Received:2016-06-30 Revised:2016-06-30 Online:2017-07-15 Published:2017-07-07
  • Contact: KANG Yan
  • About author:-
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摘要: 基物质分解是双能CT重建的重要步骤,其中双物质分解是常用的分解模型之一,该模型的核心关键是计算分解系数投影.为了更快计算它,提出了基于误差反馈梯度下降的双能CT双物质分解算法和基于Armijo-Goldstein梯度下降的双能CT双物质分解算法.由于计算了梯度下降步长,这两种方法能快速迭代求解基物质分解系数投影.同时他们有效地解决了双能CT重建的非线性问题.仿真实验结果显示,与传统查表匹配法相比,这两种算法稳定收敛,计算速度快,重建精度高,对临床应用有重要的意义.在重建结果精度近似的情况下,基于Armijo-Goldstein梯度下降的算法采用不精确线性搜索步长,因此它的运行速度更快.

关键词: 双能CT, 双物质分解, 梯度下降, 图像重建, 计算步长

Abstract: Basis material decomposition is a very essential step in dual-energy CT (DECT) reconstruction and two-material decomposition is one of the most common model whose key point is to obtain the projections of decomposition coefficient. To improve the speed of it, two-material decomposition algorithms were proposed, which are the dual-energy CT based on the error feedback gradient descent method and the Armijo-Goldstein rule gradient descent method, respectively. These two methods were able to get the projections of decomposition coefficient quickly because of the computed step size in gradient descent. Moreover, the nonlinear problem in dual-energy CT reconstruction was also effectively and efficiently solved by using the proposed methods. Simulation results indicated that compared to the projection matching method, the two proposed methods can get stable convergence and high reconstruction precision with a short span of time, which has an important significance to the clinical application. With the same reconstruction precision, the algorithm based on the Armijo-Goldstein rule gradient descent is faster, using the inexact linear search step size.

Key words: dual-energy CT, two-material decomposition, gradient descent, image reconstruction, computed step size

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