Presentation
7 March 2022 Computer-aided detection system for automated discrimination of precancerous and cancerous from healthy oral tissue based on multispectral autofluorescence lifetime imaging endoscopy
Author Affiliations +
Abstract
Multispectral autofluorescence lifetime imaging (maFLIM) endoscopy can be used to clinically image a plurality of metabolic and biochemical autofluorescence biomarkers of oral precancer and cancer. We tested the hypothesis that maFLIM-derived autofluorescence biomarkers can be used as features in machine-learning models to automatically discriminate precancerous and cancerous from healthy oral tissue. Clinical widefield maFLIM endoscopy images of cancerous and precancerous oral lesions from 57 patients were acquired and used to develop and validate a computer-aided detection (CAD) system. This study demonstrates the potentials of a maFLIM endoscopy-based CAD system for automated in situ clinical detection of oral precancer and cancer.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Elvis Duran, Shuna Cheng, Rodrigo Cuenca, Beena Ahmed, Jim Ji, Vladislav V. Yakovlev, Mathias Martinez, Moustafa Al-Khalil, Hussain Al-Enazi, Y.S. Lisa Cheng, John Wright, Carlos Busso, and Javier Jo "Computer-aided detection system for automated discrimination of precancerous and cancerous from healthy oral tissue based on multispectral autofluorescence lifetime imaging endoscopy", Proc. SPIE PC11935, Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2022, PC1193506 (7 March 2022); https://doi.org/10.1117/12.2608818
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KEYWORDS
Endoscopy

Multispectral imaging

Tissues

Imaging systems

Computer-aided diagnosis

Cancer

Computing systems

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