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Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study
Endoscopy has been widely used in diagnosing gastrointestinal mucosal lesions. However, there are still lack of objective endoscopic criteria. Linked color imaging (LCI) is newly developed endoscopic technique which enhances color contrast. Thus, we investigated the clinical application of LCI and f...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5027569/ https://www.ncbi.nlm.nih.gov/pubmed/27641243 http://dx.doi.org/10.1038/srep33473 |
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author | Sun, Xiaotian Dong, Tenghui Bi, Yiliang Min, Min Shen, Wei Xu, Yang Liu, Yan |
author_facet | Sun, Xiaotian Dong, Tenghui Bi, Yiliang Min, Min Shen, Wei Xu, Yang Liu, Yan |
author_sort | Sun, Xiaotian |
collection | PubMed |
description | Endoscopy has been widely used in diagnosing gastrointestinal mucosal lesions. However, there are still lack of objective endoscopic criteria. Linked color imaging (LCI) is newly developed endoscopic technique which enhances color contrast. Thus, we investigated the clinical application of LCI and further analyzed pixel brightness for RGB color model. All the lesions were observed by white light endoscopy (WLE), LCI and blue laser imaging (BLI). Matlab software was used to calculate pixel brightness for red (R), green (G) and blue color (B). Of the endoscopic images for lesions, LCI had significantly higher R compared with BLI but higher G compared with WLE (all P < 0.05). R/(G + B) was significantly different among 3 techniques and qualified as a composite LCI marker. Our correlation analysis of endoscopic diagnosis with pathology revealed that LCI was quite consistent with pathological diagnosis (P = 0.000) and the color could predict certain kinds of lesions. ROC curve demonstrated at the cutoff of R/(G+B) = 0.646, the area under curve was 0.646, and the sensitivity and specificity was 0.514 and 0.773. Taken together, LCI could improve efficiency and accuracy of diagnosing gastrointestinal mucosal lesions and benefit target biopsy. R/(G + B) based on pixel brightness may be introduced as a objective criterion for evaluating endoscopic images. |
format | Online Article Text |
id | pubmed-5027569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-50275692016-09-22 Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study Sun, Xiaotian Dong, Tenghui Bi, Yiliang Min, Min Shen, Wei Xu, Yang Liu, Yan Sci Rep Article Endoscopy has been widely used in diagnosing gastrointestinal mucosal lesions. However, there are still lack of objective endoscopic criteria. Linked color imaging (LCI) is newly developed endoscopic technique which enhances color contrast. Thus, we investigated the clinical application of LCI and further analyzed pixel brightness for RGB color model. All the lesions were observed by white light endoscopy (WLE), LCI and blue laser imaging (BLI). Matlab software was used to calculate pixel brightness for red (R), green (G) and blue color (B). Of the endoscopic images for lesions, LCI had significantly higher R compared with BLI but higher G compared with WLE (all P < 0.05). R/(G + B) was significantly different among 3 techniques and qualified as a composite LCI marker. Our correlation analysis of endoscopic diagnosis with pathology revealed that LCI was quite consistent with pathological diagnosis (P = 0.000) and the color could predict certain kinds of lesions. ROC curve demonstrated at the cutoff of R/(G+B) = 0.646, the area under curve was 0.646, and the sensitivity and specificity was 0.514 and 0.773. Taken together, LCI could improve efficiency and accuracy of diagnosing gastrointestinal mucosal lesions and benefit target biopsy. R/(G + B) based on pixel brightness may be introduced as a objective criterion for evaluating endoscopic images. Nature Publishing Group 2016-09-19 /pmc/articles/PMC5027569/ /pubmed/27641243 http://dx.doi.org/10.1038/srep33473 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Sun, Xiaotian Dong, Tenghui Bi, Yiliang Min, Min Shen, Wei Xu, Yang Liu, Yan Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study |
title | Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study |
title_full | Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study |
title_fullStr | Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study |
title_full_unstemmed | Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study |
title_short | Linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study |
title_sort | linked color imaging application for improving the endoscopic diagnosis accuracy: a pilot study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5027569/ https://www.ncbi.nlm.nih.gov/pubmed/27641243 http://dx.doi.org/10.1038/srep33473 |
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