Presentation + Paper
2 March 2022 Improving colorectal cancer detection by extending the near-infrared wavelength range and tissue probed depth of diffuse reflectance spectroscopy: a support vector machine approach
Author Affiliations +
Abstract
Colorectal cancer (CRC) is the second most deadly and third most common type of cancer worldwide. In this study, we assessed the improvement of the diagnostic potential of diffuse reflectance spectroscopy (DRS) for CRC detection upon extending the tissue probed depth (up to 2mm) and wavelength ranges (350-1919 nm) investigated in previous studies. We analyzed almost 3000 DR spectra (7.5 times more than previous studies) collected with 630-µm and 2500-µm source-detector distance probes by using support vector machines with potential to automate tissue classification. We achieved 96.1% sensitivity and 95.7% specificity and 0.987±0.005 AUC on tissue classification.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marcelo Saito Nogueira, Siddra Maryam, Michael Amissah, Huihui Lu, Noel Lynch, Shane Killeen, Micheal O'Riordain, and Stefan Andersson-Engels "Improving colorectal cancer detection by extending the near-infrared wavelength range and tissue probed depth of diffuse reflectance spectroscopy: a support vector machine approach", Proc. SPIE 11954, Optical Biopsy XX: Toward Real-Time Spectroscopic Imaging and Diagnosis, 1195404 (2 March 2022); https://doi.org/10.1117/12.2610497
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KEYWORDS
Tissues

Tissue optics

Colorectal cancer

Diffuse reflectance spectroscopy

Error control coding

Biomedical optics

Cancer

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