Hyperspectral imaging of diabetes mellitus skin complications
Dremin, Viktor V.; Zherebtsov, Evgenii A.; Popov, Alexey P.; Meglinski, Igor V.; Bykov, Alexander V. (2022-10-31)
Dremin, V. V., Zherebtsov, E. A., Popov, A. P., Meglinski, I. V., & Bykov, A. V. (2022). Hyperspectral imaging of diabetes mellitus skin complications. In A. Dunaev & V. Tuchin, Biomedical Photonics for Diabetes Research (1st ed., pp. 177–195). CRC Press. https://doi.org/10.1201/9781003112099-8
This is an Accepted Manuscript of a book chapter published by Routledge/CRC Press in Biomedical Photonics for Diabetes Research on 31 October 2022, available online: https://doi.org/10.1201/9781003112099. It is deposited under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
https://creativecommons.org/licenses/by-nc-nd/4.0/
https://urn.fi/URN:NBN:fi-fe2023040535199
Tiivistelmä
Abstract
Diabetes leads to protein glycation and causes dysfunction of collagen-containing tissues. The accompanying structural and functional changes of collagen significantly contribute to the development of various pathological malformations affecting the skin, blood vessels, and nerves, causing a number of complications, increasing disability risks and threat to life. The prevalence of diabetic complications is a significant public health problem with a considerable economic cost. In fact, no methods currently exist of noninvasive assessment of glycation and associated metabolic processes in biotissues or prediction of possible skin complications, e.g., ulcers, for clinical diagnosis and use by endocrinologists. Here, utilizing emerging photonics-based technology, innovative solutions in machine learning, and definitive physiological characteristics, we describe a diagnostic approach capable of evaluating the skin complications of diabetes mellitus at an early stage. The technique of polarization-based hyperspectral imaging developed in-house, accomplished by implementing an artificial neural network, provides new horizons in the study and diagnosis of age-related diseases.
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