基于扩散张量成像技术的大脑组织核磁共振电导率重构的仿真研究

Brain Tissue Conductivity Reconstruction Based on Diffusion Tensor Magnetic Resonance Imaging:A Simulation Study

将核磁共振电阻抗成像(MREIT)技术应用于人体头部大脑组织电导率重构上。采用基于径向基函数(RBF)神经网络的均质电导率重构MREIT算法,对建立在扩散张量核磁共振成像(DT-MRI)数据基础上的白质组织各向异性电导率和各向同性的灰质、脑脊液目标电导率进行重构。在五层真实形状头模型(包括头皮、颅骨、脑脊液、灰质和白质组织)上进行的仿真实验结果表明,该算法具有一定的抗噪声能力,重构的头部电导率分布图像具有较高的精确性。研究证明了MREIT技术用于头部复杂组织结构电导率重构上的合理性与可行性,在无创头部组织电导率检测领域具有潜在的应用价值。

Magnetic resonance electrical impedance tomography （MREIT） was used to reconstruct the homogeneous conductivity of the brain tissues. RBF （radius basic function）-MREIT algorithm for homogeneous conductivity reconstruction was extended to reconstruct conductivity of the anisotropic white matter based on the data from diffusion tensor magnetic resonance imaging （ DT-MRI）, as well as the target conductivity of the isotropic gray matter and CSF according to the practically physical experiment measurement. Numerical simulations were performed on the five-layer realistic head model including the isotropic CSF（cerebrospinal fluid）, gray matter and the anisotropic white matter. Present results showed that the conductivity reconstruction method had higher accuracy and better robustness against noise. The research was used to judge the feasibility, meaningfulness and reliability of the MREIT applied on the electrical impedance tomography of the complicated human head tissues.