Literature DB >> 20856274

Simple two-layer reflectance model for biological tissue applications: lower absorbing layer.

George Zonios1, Aikaterini Dimou.   

Abstract

A simple two-layer tissue reflectance model is described. This work is a continuation of our investigations on modeling reflectance from two-layered tissues that we recently initiated. In the present article, we describe a variation of a two-layer model that assumes a lower absorbing and scattering layer and an upper scattering-only layer. This two-layer configuration is a realistic model for biological tissues in the visible and near-IR spectral ranges, where the upper layer may be an epithelial layer and the lower layer is a vascularized stroma layer. Application of the model yields estimates for tissue parameters, such as the thickness of the upper layer or the absorption properties of the lower layer. These parameters are of great interest for the noninvasive study of a wide range of epithelial biological tissues. The validity range and accuracy of the model are tested on tissue phantoms in both the forward and inverse modes of application.

Mesh:

Year:  2010        PMID: 20856274     DOI: 10.1364/AO.49.005026

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  3 in total

1.  Modelling spatially-resolved diffuse reflectance spectra of a multi-layered skin model by artificial neural networks trained with Monte Carlo simulations.

Authors:  Sheng-Yang Tsui; Chiao-Yi Wang; Tsan-Hsueh Huang; Kung-Bin Sung
Journal:  Biomed Opt Express       Date:  2018-03-07       Impact factor: 3.732

2.  Verification of a two-layer inverse Monte Carlo absorption model using multiple source-detector separation diffuse reflectance spectroscopy.

Authors:  Manu Sharma; Ricky Hennessy; Mia K Markey; James W Tunnell
Journal:  Biomed Opt Express       Date:  2013-12-02       Impact factor: 3.732

3.  Modeling diffuse reflectance from homogeneous semi-infinite turbid media for biological tissue applications: a Monte Carlo study.

Authors:  George Zonios; Aikaterini Dimou
Journal:  Biomed Opt Express       Date:  2011-11-09       Impact factor: 3.732

  3 in total

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