Open Access
20 November 2018 Quantitative analysis of in vivo high-resolution microendoscopic images for the detection of neoplastic colorectal polyps
Yubo Tang, Alexandros D. Polydorides, Sharmila Anandasabapathy, Rebecca R. Richards-Kortum
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Abstract
Colonoscopy is routinely performed for colorectal cancer screening but lacks the capability to accurately characterize precursor lesions and early cancers. High-resolution microendoscopy (HRME) is a low-cost imaging tool to visualize colorectal polyps with subcellular resolution. We present a computer-aided algorithm to evaluate HRME images of colorectal polyps and classify neoplastic from benign lesions. Using histopathology as the gold standard, clinically relevant features based on luminal morphology and texture are quantified to build the classification algorithm. We demonstrate that adenomatous polyps can be identified with a sensitivity and specificity of 100% and 80% using a two-feature linear discriminant model in a pilot test set. The classification algorithm presented here offers an objective framework to detect adenomatous lesions in the colon with high accuracy and can potentially improve real-time assessment of colorectal polyps.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Yubo Tang, Alexandros D. Polydorides, Sharmila Anandasabapathy, and Rebecca R. Richards-Kortum "Quantitative analysis of in vivo high-resolution microendoscopic images for the detection of neoplastic colorectal polyps," Journal of Biomedical Optics 23(11), 116003 (20 November 2018). https://doi.org/10.1117/1.JBO.23.11.116003
Received: 23 June 2018; Accepted: 26 October 2018; Published: 20 November 2018
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Image segmentation

In vivo imaging

Quantitative analysis

Colorectal cancer

Cancer

Colon

Algorithm development

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