Presentation + Paper
4 March 2016 LED-based near infrared sensor for cancer diagnostics
Andrey Bogomolov, Vladimir Ageev, Urszula Zabarylo, Iskander Usenov, Franziska Schulte, Dmitry Kirsanov, Valeria Belikova, Olaf Minet, E. Feliksberger, I. Meshkovsky, Viacheslav Artyushenko
Author Affiliations +
Abstract
Optical spectroscopic technologies are increasingly used for cancer diagnostics. Feasibility of differentiation between malignant and healthy samples of human kidney using Fluorescence, Raman, MIR and NIR spectroscopy has been recently reported . In the present work, a simplification of NIR spectroscopy method has been studied. Traditional high-resolution NIR spectrometry was replaced by an optical sensor based on a set of light-emitting diodes at selected wavelengths as light sources and a photodiode. Two prototypes of the sensor have been developed and tested using 14 in-vitro samples of seven kidney tumor patients. Statistical evaluation of results using principal component analysis and partial least-squares discriminant analysis has been performed. Despite only partial discrimination between tumor and healthy tissue achieved by the presented new technique, the results evidence benefits of LED-based near-infrared sensing used for oncological diagnostics.

Publisher's Note: This paper, originally published on 4 March, 2016, was replaced with a corrected/revised version on 7 April, 2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andrey Bogomolov, Vladimir Ageev, Urszula Zabarylo, Iskander Usenov, Franziska Schulte, Dmitry Kirsanov, Valeria Belikova, Olaf Minet, E. Feliksberger, I. Meshkovsky, and Viacheslav Artyushenko "LED-based near infrared sensor for cancer diagnostics", Proc. SPIE 9715, Optical Diagnostics and Sensing XVI: Toward Point-of-Care Diagnostics, 971510 (4 March 2016); https://doi.org/10.1117/12.2214342
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Cited by 5 scholarly publications.
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KEYWORDS
Tumors

Sensors

Cancer

Tissues

Near infrared

Diagnostics

Data modeling

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