Near-Infrared Diffuse Optical Imaging of Blood Flow via Combining
with Tikhonov Regularization Algorithm
ZHANG Xiaojuan1,2, XU Jinrong1, GUI Zhiguo2, BAI Xin2, ZUO Jia2, LIU Yi2, SHANG Yu2
1. School of Electronic Engineering, Taiyuan Institute of Technology, Taiyuan Shanxi 030008, China;
2. School of Information and Communication Engineering, North University of China, Taiyuan Shanxi 030051, China
Abstract：Near-infrared diffuse correlation spectroscopy/tomography (DCS/DCT) is a kind of novel technologies for measurement
and imaging of the blood flow in biological tissues, and the imaging quality is substantially influenced by the image reconstruction
algorithms. There are limitations of the currently used analytical expression and finite element method, consequently impacting
the accuracy and robustness of the reconstructed blood flow imaging. Based on a new N-order linear algorithm, we proposed, in
this paper, a novel flow image reconstruction technology through combining DCT with Tikhonov regularization approach (namely
Tikhonov-DCT). This reconstruction technology permits fully utilization of tissue geometry and structure by Monte Carlo (MC)
simulation of photon information in the tissues. Moreover, Tikhonov regularization can significantly moderate ill-posed problem
occurred in image reconstruction, obtaining increased accuracy and robustness of flow imaging. The outcomes derived from the
computer simulations of realistic human head indicated that Tikhonov-DCT technology accurately exhibited the anomaly blood flow
index (BFI) and locations, with clearly edge. The proposed Tikhonov-DCT technology has potential application in optimizing the
locations and number of optical sensors, as well as in various physiological and clinical flow imaging.
