Evolution strategies for optical tomographic characterization of homogeneous media

Andreas H. Hielscher, Alexander D. Klose, J. Beuthan

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The reconstruction problem in diffuse optical tomography can be formulated as an optimization problem, in which an objective function has to be minimized. Current model-based iterative image reconstruction schemes commonly use information about the gradient of the objective function to locate the minimum. These gradient-based search algorithms often find local minima close to an initial guess, or do not converge if the gradient is very small. If the initial guess is too far from the solution, gradient-based schemes prove inefficient for finding the global minimum. In this work we introduce evolution-strategy (ES) algorithms for diffuse optical tomography. These algorithms seek to find the global minimum and are less sensitive to initial guesses and regions with small gradients. We illustrate the fundamental concepts by comparing the performance of gradient-based schemes and ES algorithms in finding optical properties (absorption coefficient μa, scattering coefficient μs, and anisotropy factor g) of a homogenous medium.

    Original languageEnglish (US)
    Pages (from-to)507-518
    Number of pages12
    JournalOptics Express
    Volume7
    Issue number13
    DOIs
    StatePublished - Dec 2000

    ASJC Scopus subject areas

    • Atomic and Molecular Physics, and Optics

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