Estimation of the optical path length factor for functional imaging of an exposed cortex by principal component analysis

Kentaro Yokoyama, Motoshi Watanabe, Eiji Okada

Research output: Contribution to journalConference article

2 Citations (Scopus)

Abstract

Activation of the cerebral cortex induces a localized change in the volume and oxygenation of the blood. Because the change in spectral reflectance of the cortex depends upon the concentration changes in oxy- and deoxy haemoglobin, multi-spectral imaging has been applied to investigate the functional activity of the exposed cortex related to oxy- and deoxy haemoglobin. However, brain tissue is a highly scattering medium, and the reflectance of cortical tissue depends on the mean optical path length of the detected light. The linear spectrographic analysis method without wavelength-dependent path length scaling may produce unreliable results in multi-spectral image analysis. In this study, we propose a method of estimating the wavelength-dependent path length factor from the principal component analysis of the multi-spectral images of the exposed cortex. The optical path-length factor estimated from the first principal component of the multi-spectral image of the cortical model and the absorption spectrum of haemoglobin agrees with that predicted by Monte Carlo simulation. The tendency of the optical path-length factor of the pig brain estimated from the first principal component of the multi-spectral images is almost the same as that of the cortical model.

Original languageEnglish
Pages (from-to)168-179
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5138
DOIs
Publication statusPublished - 2003 Jan 1
EventPhoton Migration and Diffuse-Light Imaging - Munich, Germany
Duration: 2003 Jun 222003 Jun 23

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Keywords

  • Exposed cortex
  • Monte Carlo simulation
  • Optical path-length factor
  • Principal component analysis

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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