Hyperspectral imaging of human skin aided by artificial neural networks

Abstract

We developed a compact, hand-held hyperspectral imaging system for 2D neural network-based visualization of skin chromophores and blood oxygenation. State-of-the-art micro-optic multichannel matrix sensor combined with the tunable Fabry-Perot micro interferometer enables a portable diagnostic device sensitive to the changes of the oxygen saturation as well as the variations of blood volume fraction of human skin. Generalized object-oriented Monte Carlo model is used extensively for the training of an artificial neural network utilized for the hyperspectral image processing. In addition, the results are verified and validated via actual experiments with tissue phantoms and human skin in vivo. The proposed approach enables a tool combining both the speed of an artificial neural network processing and the accuracy and flexibility of advanced Monte Carlo modeling. Finally, the results of the feasibility studies and the experimental tests on biotissue phantoms and healthy volunteers are presented.

Publication DOI: https://doi.org/10.1364/BOE.10.003545
Divisions: College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT)
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Funding Information: 1Opto-Electronics and Measurement Techniques Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, PO Box 4500, 90014 Oulu, Finland 2School of Engineering and Computer Science, Victoria University of Wellington,
Additional Information: © 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement Funding: Academy of Finland (290596, 314369, 318281); Ministry of Science and Higher Education of Russian Federation (0035-2019-0014)
Uncontrolled Keywords: Biotechnology,Atomic and Molecular Physics, and Optics
Publication ISSN: 2156-7085
Last Modified: 14 May 2024 07:19
Date Deposited: 18 Dec 2020 14:52
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2019-06-24
Accepted Date: 2019-06-11
Authors: Zherebtsov, Evgeny
Dremin, Viktor (ORCID Profile 0000-0001-6974-3505)
Popov, Alexey
Doronin, Alexander
Kurakina, Daria
Kirillin, Mikhail
Meglinski, Igor (ORCID Profile 0000-0002-7613-8191)
Bykov, Alexander

Download

[img]

Version: Published Version

License: ["licenses_description_other" not defined]

| Preview

Export / Share Citation


Statistics

Additional statistics for this record