摘要
磁声成像技术是一种利用电磁场及超声场耦合成像的技术,能以超声分辨率来显示生物组织电特性分布参数。为具体分析一些检测条件对磁声成像系统重建的影响,获取高分辨率电导率图像,对磁声成像系统矩阵特征值差异性进行仿真研究。从磁声成像声源产生原理出发,分析磁声声源的特性,并分别针对不同声换能器个数、不同磁声信号接收采样角度及不同带宽换能器的条件,建立磁声成像系统矩阵模型;以矩阵模型为基础,分别计算系统矩阵的特征值,利用截断奇异值方法对各条件下获取的磁声信号进行图像重建。结果表明,换能器个数及换能器带宽特性对电导率信息的重建影响很大,而接收角度对接收电导率信息影响不大,但接收角度会影响求解域,从而造成磁声信号接收不全,重建的电导率图像失真。本研究将对磁声成像实验设计和后续应用提供研究基础。
Magneto-acoustic tomography(MAT)is an imaging technology using the coupling of electromagnetic field and ultrasonic field,which can display the electrical characteristics distribution of biological tissues with ultrasonic resolution.In order to analyze the influence of some detection conditions on the reconstruction of MAT and obtain a high-resolution conductivity image,the eigenvalue difference of MAT is simulated.Based on the principle of acoustic source,the system matrix of MAT is established for different number of acoustic transducers,different acquisition angles and two different bandwidth transducers.Based on the matrix model,the eigenvalues of system matrix are calculated,and the TSVD method is used to reconstruct the conductivity image.The results show that the number of transducers and the bandwidth characteristics of transducers have great influence on the reconstruction of conductivity information,while the acquisition angle has little effect on the conductivity information.However,the acquisition angle will affect the field of image,resulting in incomplete reception of MAT signal and distortion of reconstructed conductivity image.This paper will provide a reference for the experiment design and subsequent applications of MAT.
作者
马任
周晓青
张顺起
殷涛
刘志朋
Ma Ren;Zhou Xiaoqing;Zhang Shunqi;Yin Tao;Liu Zhipeng(Institute of Biomedical Engineering,Chinese Academy of Medical Sciences&Peking Union Medical College,Tianjin 300192,China)
出处
《电工技术学报》
EI
CSCD
北大核心
2021年第4期724-731,共8页
Transactions of China Electrotechnical Society
基金
国家自然科学基金(61701545,81772004,81772003,81927806)
天津市自然科学基金(19JCQNJC12900)
中国医学科学院医学与健康科技创新工程协同创新团队(2017-I2M-3-020)资助项目。
关键词
磁声成像逆问题
特征值
系统矩阵
电导率分布
Magnetoacoustic tomography
inverse problem
eigenvalues
system matrix
distribution of electrical conductivity