Estimation of skin optical parameters for real-time hyperspectral imaging applications

Asgeir Bjorgan; Matija Milanic; Lise Lyngsnes Randeberg

doi:10.1117/1.JBO.19.6.066003

4 June 2014 Estimation of skin optical parameters for real-time hyperspectral imaging applications

Asgeir Bjorgan, Matija Milanic, Lise Lyngsnes Randeberg

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Journal of Biomedical Optics, Vol. 19, Issue 6, 066003 (June 2014). https://doi.org/10.1117/1.JBO.19.6.066003

Abstract

Hyperspectral imaging combines high spectral and spatial resolution in one modality. This imaging technique is a promising tool for objective medical diagnostics. However, to be attractive in a clinical setting, the technique needs to be fast and accurate. Hyperspectral imaging can be used to analyze tissue properties using spectroscopic methods, and is thus useful as a general purpose diagnostic tool. We combine an analytic diffusion model for photon transport with real-time analysis of the hyperspectral images. This is achieved by parallelizing the inverse photon transport model on a graphics processing unit to yield optical parameters from diffuse reflectance spectra. The validity of this approach was verified by Monte Carlo simulations. Hyperspectral images of human skin in the wavelength range 400–1000 nm, with a spectral resolution of 3.6 nm and 1600 pixels across the field of view (Hyspex VNIR-1600), were used to develop the presented approach. The implemented algorithm was found to output optical properties at a speed of 3.5 ms per line of image data. The presented method is thus capable of meeting the defined real-time requirement, which was 30 ms per line of data.The algorithm is a proof of principle, which will be further developed.

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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Asgeir Bjorgan, Matija Milanic, and Lise Lyngsnes Randeberg "Estimation of skin optical parameters for real-time hyperspectral imaging applications," Journal of Biomedical Optics 19(6), 066003 (4 June 2014). https://doi.org/10.1117/1.JBO.19.6.066003

Published: 4 June 2014

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Cited by 64 scholarly publications and 3 patents.

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KEYWORDS

Skin

Absorption

Monte Carlo methods

Hyperspectral imaging

Blood

Diffusion

3D modeling

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