Subdiffusion reflectance spectroscopy to measure tissue ultrastructure and microvasculature: model and inverse algorithm

Andrew J. Radosevich; Adam Eshein; The-Quyen Nguyen; Vadim Backman

doi:10.1117/1.JBO.20.9.097002

28 September 2015 Subdiffusion reflectance spectroscopy to measure tissue ultrastructure and microvasculature: model and inverse algorithm

Andrew J. Radosevich, Adam Eshein, The-Quyen Nguyen, Vadim Backman

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Journal of Biomedical Optics, Vol. 20, Issue 9, 097002 (September 2015). https://doi.org/10.1117/1.JBO.20.9.097002

Abstract

Reflectance measurements acquired from within the subdiffusion regime (i.e., lengthscales smaller than a transport mean free path) retain much of the original information about the shape of the scattering phase function. Given this sensitivity, many models of subdiffusion regime light propagation have focused on parametrizing the optical signal through various optical and empirical parameters. We argue, however, that a more useful and universal way to characterize such measurements is to focus instead on the fundamental physical properties, which give rise to the optical signal. This work presents the methodologies that used to model and extract tissue ultrastructural and microvascular properties from spatially resolved subdiffusion reflectance spectroscopy measurements. We demonstrate this approach using ex-vivo rat tissue samples measured by enhanced backscattering spectroscopy.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Andrew J. Radosevich, Adam Eshein, The-Quyen Nguyen, and Vadim Backman "Subdiffusion reflectance spectroscopy to measure tissue ultrastructure and microvasculature: model and inverse algorithm," Journal of Biomedical Optics 20(9), 097002 (28 September 2015). https://doi.org/10.1117/1.JBO.20.9.097002

Published: 28 September 2015

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