Open Access
11 September 2015 Hyperspectral imaging for detection of arthritis: feasibility and prospects
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Abstract
Rheumatoid arthritis (RA) is a disease that frequently leads to joint destruction. It has a high incidence rate worldwide, and the disease significantly reduces patients’ quality of life. Detecting and treating inflammatory arthritis before structural damage to the joint has occurred is known to be essential for preventing patient disability and pain. Existing diagnostic technologies are expensive, time consuming, and require trained personnel to collect and interpret data. Optical techniques might be a fast, noninvasive alternative. Hyperspectral imaging (HSI) is a noncontact optical technique which provides both spectral and spatial information in one measurement. In this study, the feasibility of HSI in arthritis diagnostics was explored by numerical simulations and optimal imaging parameters were identified. Hyperspectral reflectance and transmission images of RA and normal human joint models were simulated using the Monte Carlo method. The spectral range was 600 to 1100 nm. Characteristic spatial patterns for RA joints and two spectral windows with transmission were identified. The study demonstrated that transmittance images of human joints could be used as one parameter for discrimination between arthritic and unaffected joints. The presented work shows that HSI is a promising imaging modality for the diagnostics and follow-up monitoring of arthritis in small joints.
Milanic, Paluchowski, and Randeberg: Hyperspectral imaging for detection of arthritis: feasibility and prospects
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.
Matija Milanic, Lukasz A. Paluchowski, and Lise L. Randeberg "Hyperspectral imaging for detection of arthritis: feasibility and prospects," Journal of Biomedical Optics 20(9), 096011 (11 September 2015). https://doi.org/10.1117/1.JBO.20.9.096011
Published: 11 September 2015
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CITATIONS
Cited by 16 scholarly publications and 1 patent.
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KEYWORDS
Transmittance

Reflectivity

Hyperspectral imaging

Tissues

Monte Carlo methods

Absorption

Atomic force microscopy

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