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Related Experiment Videos

Perturbation theory for diffuse light transport in complex biological tissues

M R Ostermeyer1, S L Jacques

  • 1Laser Biology Research Laboratory, University of Texas, M. D. Anderson Cancer Center, Houston 77030, USA.

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|January 1, 1997
PubMed
Summary

A new perturbation theory models light transport in turbid media. It uses virtual sources to describe scattering and absorption, improving inverse problem resolution.

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Area of Science:

  • Biomedical Optics
  • Photonics
  • Medical Imaging

Background:

  • Optical transport in turbid media is crucial for applications like medical imaging.
  • Understanding light scattering and absorption is key to accurate modeling.
  • Existing models face challenges with inhomogeneities and complex light sources.

Purpose of the Study:

  • To develop a novel perturbation theory for the forward problem of optical transport.
  • To account for both scattering and absorption in inhomogeneous turbid media.
  • To analyze the impact of perturbations on light fields for inverse problem applications.

Main Methods:

  • Developed a perturbation theory based on the concept of virtual sources.
  • Modeled absorbing perturbations using volume distributions of virtual sources (monopole effect).

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  • Modeled scattering objects using surface distributions of virtual sources (dipolelike effect).

    • Main Results:

    • The theory is applicable to steady-state and modulated light.
    • Distinguished between monopole perturbations from absorption and dipolelike perturbations from scattering.
    • Identified ambiguities between scattering and absorbing perturbations for source-detector placement.

    Conclusions:

    • Virtual source concept clarifies ambiguities in optical tomography inverse problems.
    • Surface effects from sharp boundaries of scattering objects present numerical challenges.
    • These surface effects offer opportunities to enhance the resolution of inverse algorithms.