摘要
颅脑磁感应断层成像技术(BMIT)是一种非接触、无创的新兴颅脑医学成像技术,图像重建算法是提高重建图像质量的关键。依据BMIT反投影算法和迭代算法,设计出一套基于滤波反投影的脑磁感应迭代重建方法。首先根据滤波反投影重建算法原理,给出初始电导率分布,其次基于电导率变化敏感性加权计算滤波反投影矩阵,最后利用一步牛顿迭代构成滤波反投影迭代重建算法,通过设置理想条件数G来修正Hessian矩阵,改善重建过程的病态程度,并对待重建数据进行标准化位置校正处理。实验结果表明,该算法成像速度快,重建出的图像具有较高分辨率,能够准确反映成像区域内仿真病变的大小及位置信息,且轮廓清晰,为颅脑磁感应断层成像技术应用于临床监护奠定了基础。
Brain magnetic induction tomography（ BMIT） is a non-contact,non-invasive,emerging brain medical imaging technique.Image reconstruction algorithm is the key to improve the quality of the reconstructed image. In this paper,on the basis of BMIT backprojection algorithm and iterative algorithm,a set of brain magnetic induction iterative reconstruction method is designed based on filtered back-projection. Firstly,according to the principle of the filtered back-projection reconstruction algorithm,the initial conductivity distribution is given. Secondly,the filtered back-projection matrix is calculated with weight based on the sensitivity of conductivity changes. Finally,one-step Newton iteration is adopted to construct the filtered back-projection iteration reconstruction algorithm,and through setting the number of ideal conditions G the Hessian matrix is corrected,the morbid degree of the reconstruction process is improved,and the standardized position correction processing is performed on the data to be reconstructed. Experiment results demonstrate that the proposed algorithm has high imaging speed,the reconstructed image has high resolution; the propose algorithm can accurately reflect the size and location information of the simulated lesions in the imaging area,and the image outline is clear. This study lays a foundation for the application of brain magnetic induction tomography in clinical care.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2016年第11期2445-2451,共7页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(51377109)
辽宁省教育厅重点实验室基础研究项目(LZ2014011)资助
关键词
颅脑磁感应断层成像
滤波反投影
迭代算法
待重建数据
brain magnetic induction tomography（BMIT）
filtered back-projection
iterative algorithm
data to be reconstructed
