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10.1117/1.JBO.20.9.097002

http://scihub22266oqcxt.onion/10.1117/1.JBO.20.9.097002
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C4963470!4963470!26414387
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suck abstract from ncbi


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pmid26414387      J+Biomed+Opt 2015 ; 20 (9): ä
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  • Subdiffusion reflectance spectroscopy to measure tissue ultrastructure and microvasculature: model and inverse algorithm #MMPMID26414387
  • Radosevich AJ; Eshein A; Nguyen TQ; Backman V
  • J Biomed Opt 2015[Sep]; 20 (9): ä PMID26414387show ga
  • 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.
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