Hyperspectral signature analysis of skin parameters

Saurabh Vyas, Amit Banerjee, Luis Garza, Sewon Kang, Philippe Burlina

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The temporal analysis of changes in biological skin parameters, including melanosome concentration, collagen concentration and blood oxygenation, may serve as a valuable tool in diagnosing the progression of malignant skin cancers and in understanding the pathophysiology of cancerous tumors. Quantitative knowledge of these parameters can also be useful in applications such as wound assessment, and point-of-care diagnostics, amongst others. We propose an approach to estimate in vivo skin parameters using a forward computational model based on Kubelka-Munk theory and the Fresnel Equations. We use this model to map the skin parameters to their corresponding hyperspectral signature. We then use machine learning based regression to develop an inverse map from hyperspectral signatures to skin parameters. In particular, we employ support vector machine based regression to estimate the in vivo skin parameters given their corresponding hyperspectral signature. We build on our work from SPIE 2012, and validate our methodology on an in vivo dataset. This dataset consists of 241 signatures collected from in vivo hyperspectral imaging of patients of both genders and Caucasian, Asian and African American ethnicities. In addition, we also extend our methodology past the visible region and through the short-wave infrared region of the electromagnetic spectrum. We find promising results when comparing the estimated skin parameters to the ground truth, demonstrating good agreement with well-established physiological precepts. This methodology can have potential use in non-invasive skin anomaly detection and for developing minimally invasive pre-screening tools.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2013
Subtitle of host publicationComputer-Aided Diagnosis
DOIs
StatePublished - Jun 5 2013
EventMedical Imaging 2013: Computer-Aided Diagnosis - Lake Buena Vista, FL, United States
Duration: Feb 12 2013Feb 14 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8670
ISSN (Print)0277-786X

Other

OtherMedical Imaging 2013: Computer-Aided Diagnosis
CountryUnited States
CityLake Buena Vista, FL
Period2/12/132/14/13

Keywords

  • Blood oxygenation
  • Collagen
  • Hyperspectral imaging
  • Melanosomes
  • Support vector regression

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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