Paper
7 December 2021 Optimization of tissue classification for colorectal cancer detection using support vector machines and diffuse reflectance spectroscopy
Author Affiliations +
Abstract
Optimizing support vector machine models for colorectal cancer detection using diffuse reflectance spectroscopy at extended wavelength ranges and tissue layers up to 2mm deep achieved 96.1% sensitivity and 95.7% specificity on tissue classification.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marcelo Saito Nogueira, Michael Amissah, Siddra Maryam, Noel Lynch, Shane Killeen, Michael O'Riordain, and Stefan Andersson-Engels "Optimization of tissue classification for colorectal cancer detection using support vector machines and diffuse reflectance spectroscopy", Proc. SPIE 11919, Translational Biophotonics: Diagnostics and Therapeutics, 1191929 (7 December 2021); https://doi.org/10.1117/12.2615033
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KEYWORDS
Tissues

Error control coding

Tissue optics

Colorectal cancer

Cancer

Diffuse reflectance spectroscopy

Tumor growth modeling

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