Iterative reconstruction scheme for optical tomography based on the equation of radiative transfer

Alexander D. Klose, Andreas H. Hielscher

    Research output: Contribution to journalArticlepeer-review

    Abstract

    We report on the development of an iterative image reconstruction scheme for optical tomography that is based on the equation of radiative transfer. Unlike the commonly applied diffusion approximation, the equation of radiative transfer accurately describes the photon propagation in turbid media without any limiting assumptions regarding the optical properties. The reconstruction scheme consists of three major parts: (1) a forward model that predicts the detector readings based on solutions of the time-independent radiative transfer equation, (2) an objective function that provides a measure of the differences between the detected and the predicted data, and (3) an updating scheme that uses the gradient of the objective function to perform a line minimization to get new guesses of the optical properties. The gradient is obtained by employing an adjoint differentiation scheme, which makes use of the structure of the finite-difference discrete-ordinate formulation of the transport forward model. Based on the new guess of the optical properties a new forward calculation is performed to get new detector predictions. The reconstruction process is completed when the minimum of the objective function is found within a defined error. To illustrate the performance of the code we present initial reconstruction results based on simulated data.

    Original languageEnglish (US)
    Pages (from-to)1698-1707
    Number of pages10
    JournalMedical Physics
    Volume26
    Issue number8
    DOIs
    StatePublished - Aug 1999

    Keywords

    • Adjoint differentiation
    • Discrete ordinates
    • Equation of radiative transfer
    • Finite difference
    • Inverse problems
    • Optical tomography
    • Turbid media
    • Upwind scheme

    ASJC Scopus subject areas

    • Biophysics
    • Radiology Nuclear Medicine and imaging

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