Wang Bingyuan, Zhang Yao, Liu Dongyuan, Pan Tiantian, Liu Yang, Bai Lu, Zhou Zhongxing, Jiang Jingying, Gao Feng
Tianjin University, College of Precision Instrument and Optoelectronics Engineering, No. 92 Weijin Road, Tianjin, China, 300072.
Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, No. 92 Weijin Road, Tianjin, China, 300072.
Biomed Opt Express. 2020 May 13;11(6):3025-3042. doi: 10.1364/BOE.386567. eCollection 2020 Jun 1.
High density diffuse optical tomography has become increasingly important to detect underlying neuronal activities. Conventional methods first estimate the time courses of the changes in the absorption coefficients for all the voxels, and then estimate the hemodynamic response function (HRF). Activation-level maps are extracted at last based on this HRF. However, the error propagation among the successive processes degrades and even misleads the final results. Besides, the computation burden is heavy. To address the above problems, a direct method is proposed in this paper to simultaneously estimate the HRF and the activation-level maps from the boundary fluxes. It is assumed that all the voxels in the same activated brain region share the same HRF but differ in the activation levels, and no prior information is imposed on the specific shape of the HRF. The dynamic simulation and phantom experiments demonstrate that the proposed method outperforms the conventional one in terms of the estimation accuracy and computation speed.
高密度扩散光学层析成像在检测潜在神经元活动方面变得越来越重要。传统方法首先估计所有体素吸收系数变化的时间进程，然后估计血流动力学响应函数（HRF）。最后基于此HRF提取激活水平图。然而，连续过程中的误差传播会降低甚至误导最终结果。此外，计算负担很重。为了解决上述问题，本文提出了一种直接方法，从边界通量中同时估计HRF和激活水平图。假设同一激活脑区的所有体素共享相同的HRF，但激活水平不同，并且不对HRF的特定形状施加先验信息。动态模拟和模型实验表明，所提出的方法在估计精度和计算速度方面优于传统方法。
