@inproceedings{e3ba5ab2ad864f59a614777e9d1eb1b6,
title = "Hyperspecral skin imaging with artificial neural networks validated by optical biotissue phantoms",
abstract = "State-of-the-art micro-optic multichannel matrix sensor combined with the tunable Fabry-Perot micro interferometer enables a compact diagnostic device sensitive to the changes of the oxygen saturation as well as the blood volume fraction of human skin. The possibility of using Monte-Carlo modelling for neural network training in the problem of hyperspectral image processing has been demonstrated and validated using biotissue phantom and human skin in vivo. The proposed approach enables a tool combining both the speed of neural network processing and the accuracy and flexibility of Monte-Carlo modelling.",
author = "Alexander Bykov and Evgeny Zherebtsov and Viktor Dremin and Alexey Popov and Alexander Doronin and Igor Meglinski",
note = "Funding Information: Authors acknowledge the support of the Academy of Finland (grants: 290596, 296408). Publisher Copyright: {\textcopyright} OSA 2019 {\textcopyright} 2019 The Author(s); Computational Optical Sensing and Imaging, COSI 2019 ; Conference date: 24-06-2019 Through 27-06-2019",
year = "2019",
doi = "10.1364/COSI.2019.CW1A.3",
language = "English",
isbn = "978-1-943580-63-7",
series = "Optics InfoBase Conference Papers",
publisher = "Optica Publishing Group",
booktitle = "Computational Optical Sensing and Imaging",
address = "United States",
}