Monte Carlo analysis of near-infrared light propagation in a neonatal head model

Shuhei Eda, Eiji Okada

    Research output: Contribution to journalArticle

    2 Citations (Scopus)

    Abstract

    In brain function measurement using near-infrared light, it is very important to make a theoretical analysis of light propagation in the head tissue, since it is impossible to measure the effect of optical fiber arrangement on the region of measurement or its sensitivity. The Monte Carlo method is widely used in the analysis of near-infrared light propagation in biological tissue, since it allows light propagation analysis of heterogeneous tissue by a relatively simple algorithm. In this study, a model simulating the cross-sectional structure of the neonatal head is constructed by using square elements, and the light propagation is analyzed. First, the variance-reduction (VR) method and the delta-scattering (DS) method, which are typical algorithms of the Monte Carlo method, are applied to the model composed of square elements, and the results of the analysis and the computation time for light propagation are compared and discussed. It is shown that the DS method is useful for a model composed of small square elements, since the computation time depends little on the size of the elements. As a result of analysis of light propagation in the neonatal head model using the DS method, we see that light propagation is greatly affected by the heterogeneity of the head tissue.

    Original languageEnglish
    Pages (from-to)60-69
    Number of pages10
    JournalSystems and Computers in Japan
    Volume35
    Issue number9
    DOIs
    Publication statusPublished - 2004 Aug 1

    Keywords

    • Brain function measurement
    • Light propagation analysis
    • Monte Carlo method
    • Near-infrared spectroscopy

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Information Systems
    • Hardware and Architecture
    • Computational Theory and Mathematics

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