Presentation
5 March 2021 Colorectal cancer assessment using optical coherence tomography catheter and deep learning
Author Affiliations +
Abstract
In this study, we propose to combine miniaturized optical coherence tomography (OCT) catheter with pattern recognition (PR) OCT for differentiation of normal from neoplastic colorectal tissue in real-time. The OCT catheter has a lateral resolution of 17.15 um and an axial resolution of 6 um. The PR-OCT system is trained by RetinaNet for pattern recognition tasks. Our method leverages the recent advancement in object detection, which localizes and classifies the diagnostic features at real-time, and the integration of an endoscopy, which promises future in vivo studies. According to our previous reports, a sensitivity of 100% and specificity of 99.7% can be reached.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongbo Luo, Yifeng Zeng, Shuying Li, Chao Zhou, and Quing Zhu "Colorectal cancer assessment using optical coherence tomography catheter and deep learning", Proc. SPIE 11630, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXV, 116300W (5 March 2021); https://doi.org/10.1117/12.2583844
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KEYWORDS
Optical coherence tomography

Colorectal cancer

Endoscopy

Pattern recognition

Tissues

In vivo imaging

Neural networks

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