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Hyperspectral imaging of diabetes mellitus skin complications

  • Viktor V. Dremin*
  • , Evgenii A. Zherebtsov
  • , Alexey P. Popov
  • , Igor V. Meglinski
  • , Alexander V. Bykov
  • *Corresponding author for this work
    • Aston University
    • Orel State University Named after I.S. Turgenev
    • University of Oulu

    Research output: Chapter in Book/Report/Conference proceeding › Chapter or book article › Scientific › peer-review

    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.
    Original languageEnglish
    Title of host publicationBiomedical Photonics for Diabetes Research
    EditorsAndrey Dunaev, Valery Tuchin
    PublisherCRC Press
    Pages177-195
    Number of pages19
    ISBN (Electronic)978-1-00-073561-1, 978-1-00-311209-9
    ISBN (Print)978-0-367-63091-1
    DOIs
    Publication statusPublished - 26 Oct 2022
    MoE publication typeA3 Part of a book or another research book

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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