Research Papers: Sensing

Estimating physiological skin parameters from hyperspectral signatures

[+] Author Affiliations
Saurabh Vyas

Johns Hopkins University, Applied Physics Laboratory, Laurel, Maryland 20723

Johns Hopkins University, Department of Biomedical Engineering, Baltimore, Maryland 21218

Amit Banerjee

Johns Hopkins University, Applied Physics Laboratory, Laurel, Maryland 20723

Philippe Burlina

Johns Hopkins University, Applied Physics Laboratory, Laurel, Maryland 20723

Johns Hopkins University, Department of Computer Science, Baltimore, Maryland 21218

Johns Hopkins University, School of Medicine, Baltimore, Maryland 21287

J. Biomed. Opt. 18(5), 057008 (May 30, 2013). doi:10.1117/1.JBO.18.5.057008
History: Received January 3, 2013; Revised April 10, 2013; Accepted April 11, 2013
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Abstract.  We describe an approach for estimating human skin parameters, such as melanosome concentration, collagen concentration, oxygen saturation, and blood volume, using hyperspectral radiometric measurements (signatures) obtained from in vivo skin. We use a computational model based on Kubelka-Munk theory and the Fresnel equations. This model forward maps the skin parameters to a corresponding multiband reflectance spectra. Machine-learning-based regression is used to generate the inverse map, and hence estimate skin parameters from hyperspectral signatures. We test our methods using synthetic and in vivo skin signatures obtained in the visible through the short wave infrared domains from 24 patients of both genders and Caucasian, Asian, and African American ethnicities. Performance validation shows promising results: good agreement with the ground truth and well-established physiological precepts. These methods have potential use in the characterization of skin abnormalities and in minimally-invasive prescreening of malignant skin cancers.

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© 2013 Society of Photo-Optical Instrumentation Engineers

Topics

Reflectivity ; Skin

Citation

Saurabh Vyas ; Amit Banerjee and Philippe Burlina
"Estimating physiological skin parameters from hyperspectral signatures", J. Biomed. Opt. 18(5), 057008 (May 30, 2013). ; http://dx.doi.org/10.1117/1.JBO.18.5.057008


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