Fast and robust extraction of optical and morphological properties of human skin using a hybrid stochastic–deterministic algorithm: Monte-Carlo simulation study

A hybrid deterministic–stochastic algorithm combining the simplex method (SM) and a genetic algorithm (GA) was applied to the problem of extracting the optical and morphological properties of human skin (HSOMPs) from visual reflectance spectroscopy data. The results using the GA-SM hybrid algorithm...

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Bibliographic Details
Published in:Lasers in medical science Vol. 25; no. 5; pp. 733 - 741
Main Author: Choi, Seung Ho
Format: Journal Article
Language:English
Published: London Springer-Verlag 01.09.2010
Springer Nature B.V
Subjects:
Algorithms
Computer Simulation
Dentistry
Extraction
Genetic algorithms
Human
Humans
Lasers
Low-Level Light Therapy
Medical science
Medicine
Medicine & Public Health
Models, Biological
Monte Carlo Method
Monte Carlo methods
Monte Carlo simulation
Morphology
Optical Devices
Optical Phenomena
Optical properties
Optics
Original Article
Photonics
Port-Wine Stain - pathology
Port-Wine Stain - physiopathology
Port-Wine Stain - radiotherapy
Quantum Optics
Skin
Skin - anatomy & histology
Skin - radiation effects
Skin Physiological Phenomena
Spectrum analysis
Stochastic models
Stochastic Processes
Visible reflectance spectroscopy
Genetic algorithm
Diffusion approximation model
Simplex method
Wavelength selection method
ISSN:0268-8921, 1435-604X, 1435-604X
Online Access:Get full text
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Description
Summary:A hybrid deterministic–stochastic algorithm combining the simplex method (SM) and a genetic algorithm (GA) was applied to the problem of extracting the optical and morphological properties of human skin (HSOMPs) from visual reflectance spectroscopy data. The results using the GA-SM hybrid algorithm adopting tournament selection and selecting new sets of HSOMPs were compared with those using other conventional optimization algorithms that have generally been used for the extraction of HSOMPs. Monte-Carlo simulation showed that the suggested GA-SM hybrid algorithm enhanced the stability of the inverse solutions and computational efficiency.
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ISSN:0268-8921
1435-604X
1435-604X
DOI:10.1007/s10103-010-0793-x