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Proceedings Paper

Comparison of classification methods of Barret’s and dysplasia in the esophagus from in vivo optical coherence tomography images
Author(s): Christos Photiou; George Plastiras; Guillermo Tearney; Costas Pitris
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Paper Abstract

Endoscopic Optical Coherence Tomography (EOCT) systems can perform in vivo, real-time, high-resolution imaging of the human esophagus and, thus, play an important role in the earlier diagnosis and better prognosis of esophageal diseases such as Barrett’s, dysplasia and adenocarcinoma. However, the high image throughput and massive data volumes make manual evaluation of the generated information extremely difficult. Unfortunately, the algorithms, developed thus far, have not been able to provide effective computer-aided diagnosis. In this study, we compare different machine learning methods for tissue segmentation and classification of esophageal tissue in in vivo OCT images. An automated algorithm was developed, capable of discriminating normal tissue from Barrett’s Esophagus (BE) and dysplasia. The classification was based on various features of the epithelium, extracted from EOCT images, such as intensity-based statistics, the group velocity dispersion (GVD), estimated from the image speckle, and the scatterer size, calculated using the bandwidth of the correlation of the derivative (COD) method. The comparison and evaluation of various machine learning techniques has shown that a neural network based approach provided the best performance, classifying Barret’s esophagus and dysplasia, for individual A-Scans, with an accuracy of 89%.

Paper Details

Date Published: 21 February 2020
PDF: 4 pages
Proc. SPIE 11228, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV, 1122820 (21 February 2020); doi: 10.1117/12.2546299
Show Author Affiliations
Christos Photiou, Univ. of Cyprus (Cyprus)
George Plastiras, Univ. of Cyprus (Cyprus)
Guillermo Tearney, Massachusetts General Hospital and Harvard Medical School (United States)
Costas Pitris, Univ. of Cyprus (Cyprus)

Published in SPIE Proceedings Vol. 11228:
Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXIV
Joseph A. Izatt; James G. Fujimoto, Editor(s)

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