Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/155230
Title: Automatic differentiation of nonkeratinized stratified squamous epithelia and columnar epithelia through feature structure extraction using OCT
Authors: Xie, Jun
Chen, Si
Wang, Nanshuo
Wang, Lulu
Bo, En
Liu, Linbo
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Xie, J., Chen, S., Wang, N., Wang, L., Bo, E. & Liu, L. (2020). Automatic differentiation of nonkeratinized stratified squamous epithelia and columnar epithelia through feature structure extraction using OCT. Biomedical Signal Processing and Control, 60, 101919-. https://dx.doi.org/10.1016/j.bspc.2020.101919
Project: H1701a008
NRF-CRP13-332 2014-05
2018-T1-001-144
NAM/15005
Journal: Biomedical Signal Processing and Control
Abstract: As a type of precancerous lesion, metaplasia is usually considered to be associated with developing cancer. In clinical practice, surveillance of metaplastic cases usually relies on excisional biopsy followed by histological processing and analysis. As it is an invasive method accompanied by other complications, non-invasive imaging methods such as optical coherence tomography (OCT) can complement the existing method by enabling large area scanning. However, because it takes time to review large amount of data acquired from the whole suspected mucosal areas, an automatic classification method is preferred to alleviate the laboring hours and to avoid ‘sampling errors’ during image analysis. In this study, we report an automatic method to differentiate non-keratinized squamous epithelia and columnar epithelia in OCT images. A high detection accuracy is achieved by using feature structure extraction techniques in intact tissues.
URI: https://hdl.handle.net/10356/155230
ISSN: 1746-8094
DOI: 10.1016/j.bspc.2020.101919
Rights: © 2020 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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