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. © 2019 The Author(s)