Monte Carlo prediction of light propagation in realistic adult head model

Kaori Tajima, Shuhei Eda, Eiji Okada

    Research output: Contribution to journalConference article

    2 Citations (Scopus)

    Abstract

    The light propagation in the head models has been investigated to deduce the volume of the brain tissue sampled by NIR instrument. The light propagation in the adult head is strongly affected by the presence of low scattering cerebrospinal fluid (CSF) layer. Although the brain surface is folded with sulci filled with the CSF, the brain surface in the previous head models has had simple geometry such as a flat or curved surface. In this study, the light propagation in a realistic adult and neonatal head models of which geometry is generated from MRI scan of the head is predicted by Monte Carlo method. The adult and neonatal head models consist of small square elements to represent complex geometry and each element specified its scattering and absorption coefficients. The delta-scattering algorithm is implemented to keep the computation time within reasonable limit. The spatial sensitivity profiles for various source-detector spacing are predicted and the difference in the effect of the CSF on the spatial sensitivity profiles in the adult and neonatal head models is discussed. The low scattering CSF affects the light propagation in the adult head model while the distortion in spatial sensitivity profiles in the neonatal head model is not significant.

    Original languageEnglish
    Pages (from-to)49-56
    Number of pages8
    JournalProceedings of SPIE - The International Society for Optical Engineering
    Volume4160
    DOIs
    Publication statusPublished - 2000 Dec 1
    EventPhoton Migration, Diffuse Spectroscopy, and Optical Coherence Tomography: Imaging and Functional Assessment - Amsterdam, Neth
    Duration: 2000 Jul 62000 Jul 8

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics
    • Computer Science Applications
    • Applied Mathematics
    • Electrical and Electronic Engineering

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