Hybrid Monte Carlo-Diffusion method for light propagation in tissue with low scattering layer

Toshiyuki Hayashi, Yoshihiko Kashio, Eiji Okada

    Research output: Contribution to journalConference articlepeer-review

    Abstract

    Near infrared spectroscopy is increasingly being used for monitoring cerebral oxygenation and haemodynamics. Since the light in the head is strongly scattered, it is necessary to modelling the light propagation in the head to obtain the volume of tissue sampled and partial optical path length in the brain. The serious problem to calculate the light propagation in the head is the heterogeneity of tissue especially the presence of low scattering CSF layer. Since the diffusion equation no longer holds in the low scattering layer, the light propagation in the head model with low scattering layer should be analysed by Monte Carlo method or light transport equation. In this study, we propose a new approach "Hybrid Monte Carlo-Diffusion Method" to calculate the light propagation in the adult head model with a low scattering CSF layer. The light propagation in a high scattering medium is calculated by the diffusion theory and that in a low scattering CSF layer is predicted by Monte Carlo method. The results of detected intensity and mean time of flight in a simplified adult head model by the Hybrid Monte Carlo-Diffusion method agree well with those predicted by Monte Carlo method.

    Original languageEnglish
    Pages (from-to)169-175
    Number of pages7
    JournalProceedings of SPIE - The International Society for Optical Engineering
    Volume4431
    DOIs
    Publication statusPublished - 2001 Dec 1
    EventPhoton Migration, Optical Coherence Tomography, and Microscopy - Munich, Germany
    Duration: 2001 Jun 182001 Jun 21

    Keywords

    • CSF
    • Diffusion theory
    • FEM
    • Low-scattering medium
    • Monte Carlo
    • Near-infrared spectroscopy

    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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