%D 2021
%R 10.1109/SCOReD53546.2021.9652700
%O cited By 3; Conference of 19th IEEE Student Conference on Research and Development, SCOReD 2021 ; Conference Date: 23 November 2021 Through 25 November 2021; Conference Code:175986
%J 19th IEEE Student Conference on Research and Development: Sustainable Engineering and Technology towards Industry Revolution, SCOReD 2021
%L scholars15441
%X Functional near infra-red spectroscopy (fNIRs) with near infra-red light have been active research areas for both clinical and pre-clinical applications for more than three decades. The development of more advanced image reconstruction methods is required to improve the accuracy fNIRs of complex tissue structures. In this paper, the least square QR decomposition (LSQR) method for solving the inverse problem has been implemented for real fNIRs data based on working memory (WM). The sensitivity matrix is being generated using the Monte Carlo (MC) simulation. For image reconstruction, the numerical algorithm for the LSQR method is created and implemented in MATLAB. Lastly, the variation of oxy and deoxy haemoglobin levels is monitored based on absorption changes, and the findings obtained using the LSQR regularization method are in good agreement with the real fNIRs WM data. © 2021 IEEE.
%K Clinical research; Image enhancement; Inverse problems; Least squares approximations; MATLAB; Monte Carlo methods; Numerical methods, Functional near infra-red spectroscopy; Images reconstruction; Least Square; Least square QR decomposition method; MonteCarlo methods; Near infra-red spectroscopies; Near Infrared; Red light; Research areas; Working memory, Image reconstruction
%P 362-366
%T Least Square QR Decomposition Method for Solving the Inverse Problem in Functional Near Infra-Red Spectroscopy
%I Institute of Electrical and Electronics Engineers Inc.
%A A. Hussain
%A I. Faye
%A M.S. Muthuvalu
%A T. Tong Boon