Presentation + Paper
14 March 2017 Evaluation of a multi-layer diffuse reflectance spectroscopy system using optical phantoms
Author Affiliations +
Abstract
A fiber probe-based device for assessing microcirculatory parameters, especially red blood cell (RBC) tissue fraction, their oxygen saturation and speed resolved perfusion, has been evaluated using state-of-the-art multi-layer tissue simulating phantoms. The device comprises both diffuse reflectance spectroscopy (DRS) at two source-detector separations (0.4 and 1.2 mm) and laser Doppler flowmetry (LDF) and use an inverse Monte Carlo method for identifying the parameters of a multi-layered tissue model. First, model parameters affecting scattering, absorption and geometrical parameters are fitted to measured DRS spectra, then speed parameters are fitted to LDF spectra. In this paper, the accuracy of the spectral parameters is evaluated. The measured spectral shapes at the two source-detector separations were in good agreement with forward calculated spectral shapes. In conclusion, the multi-layer skin model based on spectral features of the included chromophores, can reliably estimate the tissue fraction of RBC, its oxygen saturation and the reduced scattering coefficient spectrum of the tissue. Furthermore, it was concluded that some freedom in the relative intensity difference between the two DRS channels is necessary in order to compensate for non-modeled surface structure effects.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ingemar Fredriksson, Rolf B. Saager, Anthony J. Durkin, and Tomas Strömberg "Evaluation of a multi-layer diffuse reflectance spectroscopy system using optical phantoms", Proc. SPIE 10056, Design and Quality for Biomedical Technologies X, 100560G (14 March 2017); https://doi.org/10.1117/12.2249562
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Absorption

Scattering

Oxygen

Tissues

Skin

Diffuse reflectance spectroscopy

Monte Carlo methods

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