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Steven Jacques Laboratory

Summary:

Prof. Jacques and his team are interested in biomedical optics and laser-tissue interactions. Additionally, their work involves the development of diagnostic and therapeutic devices for medicine and biology using optical technologies.

Affiliations:

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Instruments

Software

  • Computational method for determining optical scattering properties from confocal microscopy reflectance ( Algorithmic software component )

    This software is used to determine the optical properties (and by extension the distribution of scattering sites within the sample) by fitting experimentally derived curves from reflectance-mode confocal scanning laser microscopy.

    The fits from these curves provide both the scattering coefficient and the scattering anisotropy of the sample.

  • Monte Carlo simulation for photon propagation through tissue ( Algorithmic software component )

    "The Monte Carlo technique is a flexible method for simulating light propagation in tissue. The simulation is based on the random walks that photons make as they travel through tissue, which are chosen by statistically sampling the probability distributions for step size and angular deflection per scattering event. After propagating many photons, the net distribution of all the photon paths yields an accurate approximation to reality."

  • Spectroscopic reflectance analysis software ( Algorithmic software component )

    This software is used for the analysis of one dimensional light transport in skin. It accounts for superficial melanin and otherwise average, homogeneous skin tissue underneath. The software can be used to determine the amount of melanin, water, bilirubin, and beta-carotene in the sample as well as its O2 saturation from scattering data.

    The method can be applied to other tissues as well as semi-infinite, homogeneous tissue. It is also extendable to multi-path length methods using optical fiber techniques, thus allowing analysis of multi-layer skin.


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Last updated: 2012-10-22T15:09:37.804-05:00

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The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016