Determination of human skin optical properties from hyper spectral data with deep-learning neural networks (Conference Presentation)

Alexander Doronin; Igor Meglinski; Alexander V. Bykov; Holly Rushmeier

doi:10.1117/12.2289149

14 March 2018 Determination of human skin optical properties from hyper spectral data with deep-learning neural networks (Conference Presentation)

Alexander Doronin, Igor Meglinski, Alexander V. Bykov, Holly Rushmeier

Author Affiliations +

Proceedings Volume 10489, Optical Biopsy XVI: Toward Real-Time Spectroscopic Imaging and Diagnosis; 104890U (2018) https://doi.org/10.1117/12.2289149
Event: SPIE BiOS, 2018, San Francisco, California, United States

Abstract

In the current report, we present further developments of a unified Monte Carlo-based computational framework and explore the potential of the emerging deep-learning neural networks for the determination of human skin optical properties. The hyperspectral data is acquired at each pixel as a function of time, by varying the illumination/detection wavelength and polarization of light. Subsequently, the signature of the detected signal within the tissues is estimated by a deep learning algorithm with supervised training based on a Monte Carlo modelling and then fit for the scattering and absorption properties of the tissue. The algorithm provides an estimation of parameters such as distributions of melanin, blood vessels, oxygenation, assessment of hyper vascularization and metabolism which are particularly critical for assessment of darkly and lightly pigmented skin lesions including moles, freckles, vitiligo, etc. The results of simulations are compared with exact analytical solutions, phantom studies and traditional diffuse reflectance spectroscopic point measurements. The computational solution is accelerated by the graphics processing units (GPUs) in a cloud-computing environment providing near-instant access to the results of analysis.

Conference Presentation

Citation Download Citation

Alexander Doronin, Igor Meglinski, Alexander V. Bykov, and Holly Rushmeier "Determination of human skin optical properties from hyper spectral data with deep-learning neural networks (Conference Presentation)", Proc. SPIE 10489, Optical Biopsy XVI: Toward Real-Time Spectroscopic Imaging and Diagnosis, 104890U (14 March 2018); https://doi.org/10.1117/12.2289149

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available