计算物理 ›› 2010, Vol. 27 ›› Issue (6): 912-918.

• 研究论文 • 上一篇    下一篇

头部分层球模型磁感应成像正问题的解析解

何为, 李倩, 徐征, 朱金华, 何阳光, 王磊   

  1. 重庆大学 电气工程学院 输配电装备及系统安全与新技术国家重点实验室, 重庆 400044
  • 收稿日期:2009-11-19 修回日期:2010-03-19 出版日期:2010-11-25 发布日期:2010-11-25
  • 作者简介:何为(1957-),男,博士,教授,博士生导师,从事生物电磁场方面的研究,重庆大学电气工程学院电工理论与新技术研究所400044.
  • 基金资助:
    中俄国际合作项目(ISCP2007DFR30080);国家自然科学基金(50877082);重庆市自然科学基金(CSTC2009BB5204);科技部科技人员服务企业行动项目(2009GJF10025);输配电装备及系统安全与新技术国家重点实验室自主研究项目(2007DA10512709305)资助项目

Analytical Solution of Forward Problem for Magnetic Induction Tomography in a Multi-layer Sphere Brain Model

HE Wei, LI Qian, XU Zheng, ZHU Jinhua, HE Yangguang, WANG Lei   

  1. State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Electrical Engineering College, Chongqing University, Chongqing 400044, China
  • Received:2009-11-19 Revised:2010-03-19 Online:2010-11-25 Published:2010-11-25

摘要: 建立适用于磁感应成像正问题研究的头颅四层同心球模型,分别代表大脑、脑脊髓层、颅骨层和头皮层.以矢量磁位为变量,建立球坐标系下的亥姆赫兹方程,作为磁感应成像正问题的控制方程,用分离变量法求解亥姆赫兹方程,得到模型内矢量磁位的分布,进而推导出球内涡流场的分布特性,绘制出其等位线图.分析激励电流频率和幅值对感应电压的影响.仿真结果表明该解析方法可以计算磁感应成像正问题,并可作为生成逆问题灵敏度矩阵的一种快速算法.

关键词: 磁感应成像, 正问题, 解析解, 分离变量法

Abstract: A 4-layer sphere model of human head is built for the forward problem of magnetic induction tomography.The layers represent the brain,the CFS,the skull,and the scalp respectively.Taking vector magnetic potential as a variable,Helmholtz equation in a spherical coordinates is constructed as a control equation of the forward problem.A variables separation method is used to solve the equations with boundary and interface conditions.Distribution of the magnetic vector potential and eddy current in the model are obtained.Equi-potential lines of the eddy current are given.Influence of frequency and magnitude of the exciting current on the induced voltage is analyzed.The algorithm is validated by solving a forward problem of magnetic induction tomography.It can be used as a fast algorithm to generate sensitivity matrix in an inverse problem.

Key words: magnetic induction tomography, forward problems, analytical solutions, variables separation method

中图分类号: