Spectral imaging of skin: experimental observations and analyses
Author(s) -
John P. Kerekes,
Nithya R. Subramanian,
K. Kearney,
Nik Schad
Publication year - 2006
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.655756
Subject(s) - liquid crystal tunable filter , imaging spectroscopy , spectral imaging , optics , near infrared spectroscopy , image resolution , materials science , spectral bands , remote sensing , spectral resolution , cardinal point , hyperspectral imaging , computer science , optoelectronics , artificial intelligence , spectral line , physics , liquid crystal , geology , astronomy
The emergence of compact optical spectral imaging technologies has motivated the study of their use in a variety of applications, including medical diagnosis and monitoring. In particular, large format CCD focal planes in conjunction with spectrally tunable devices offer enhanced spatial information together with visible and near infrared (NIR) spectroscopic data for the passive, noninvasive, measurement of human skin and near surface tissue characteristics. One such spectral imaging system was recently developed by mating a Liquid Crystal Tunable Filter (LCTF) together with a 2048x2048 silicon CCD focal plane. This system is capable of collecting more than 30 co-registered spectral images spaced every 10 nanometers and spanning 400 to 720 nanometers. This system combines the potential of near infrared diffuse reflectance spectroscopy with the high spatial resolution of traditional optical imaging techniques. Spectral images were acquired of portions of the hands and arms of several test subjects with a variety of features observable. The observations were collected in a "light box" under controlled illumination conditions. Images of a diffuse reflectance standard and instrument dark frames were collected to allow conversion of the raw images to spectral reflectance images. This paper presents examples of the spectral images collected, instrument characteristics and performance, and results of analysis algorithms applied to the data. Results also are shown for a new algorithm extracting the saturated oxygen hemoglobin fraction from these data.
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