Open AccessA Kalman-based tomographic scheme for directly reconstructing activation levels of brain function
Author(s) -
Bingyuan Wang,
Tiantian Pan,
Yao Zhang,
Dongyuan Liu,
Jingying Jiang,
Huijuan Zhao,
Feng Gao
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.003229
Subject(s) - point spread function , computer science , functional near infrared spectroscopy , kalman filter , imaging phantom , diffuse optical imaging , tomographic reconstruction , iterative reconstruction , tomography , temporal resolution , optical tomography , set (abstract data type) , data set , image resolution , optics , algorithm , computer vision , artificial intelligence , physics , cognition , neuroscience , biology , programming language , prefrontal cortex
In functional near-infrared spectroscopy (fNIRS), the conventional indirect approaches first separately recover the spatial distribution of the changes in the optical properties at every time point, and then extract the activation levels by a time-course analysis process at every site. In the tomographic implementation of fNIRS, i.e., diffuse optical tomography (DOT), these approaches not only suffer from the ill-posedness of the optical inversions and error propagation between the two successive steps, but also fail to achieve satisfactory temporal resolution due to the requirement for a complete data set. To cope with the above adversities of the indirect approaches, we propose herein a direct approach to tomographically reconstructing the activation levels by incorporating a Kalman scheme. Dynamic simulative and phantom experiments were conducted for the performance validation of the proposed approach, demonstrating its potentials to improve the calculated images and to relax the speed limitation of the instruments.