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Recent Development of Computer Vision Technology to Improve Capsule Endoscopy
Capsule endoscopy (CE) is a preferred diagnostic method for analyzing small bowel diseases. However, capsule endoscopes capture a sparse number of images because of their mechanical limitations. Post-procedural management using computational methods can enhance image quality. Additional information,...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Gastrointestinal Endoscopy
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680009/ https://www.ncbi.nlm.nih.gov/pubmed/30786704 http://dx.doi.org/10.5946/ce.2018.172 |
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author | Park, Junseok Hwang, Youngbae Yoon, Ju-Hong Park, Min-Gyu Kim, Jungho Lim, Yun Jeong Chun, Hoon Jai |
author_facet | Park, Junseok Hwang, Youngbae Yoon, Ju-Hong Park, Min-Gyu Kim, Jungho Lim, Yun Jeong Chun, Hoon Jai |
author_sort | Park, Junseok |
collection | PubMed |
description | Capsule endoscopy (CE) is a preferred diagnostic method for analyzing small bowel diseases. However, capsule endoscopes capture a sparse number of images because of their mechanical limitations. Post-procedural management using computational methods can enhance image quality. Additional information, including depth, can be obtained by using recently developed computer vision techniques. It is possible to measure the size of lesions and track the trajectory of capsule endoscopes using the computer vision technology, without requiring additional equipment. Moreover, the computational analysis of CE images can help detect lesions more accurately within a shorter time. Newly introduced deep leaning-based methods have shown more remarkable results over traditional computerized approaches. A large-scale standard dataset should be prepared to develop an optimal algorithms for improving the diagnostic yield of CE. The close collaboration between information technology and medical professionals is needed. |
format | Online Article Text |
id | pubmed-6680009 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Korean Society of Gastrointestinal Endoscopy |
record_format | MEDLINE/PubMed |
spelling | pubmed-66800092019-08-05 Recent Development of Computer Vision Technology to Improve Capsule Endoscopy Park, Junseok Hwang, Youngbae Yoon, Ju-Hong Park, Min-Gyu Kim, Jungho Lim, Yun Jeong Chun, Hoon Jai Clin Endosc Review Capsule endoscopy (CE) is a preferred diagnostic method for analyzing small bowel diseases. However, capsule endoscopes capture a sparse number of images because of their mechanical limitations. Post-procedural management using computational methods can enhance image quality. Additional information, including depth, can be obtained by using recently developed computer vision techniques. It is possible to measure the size of lesions and track the trajectory of capsule endoscopes using the computer vision technology, without requiring additional equipment. Moreover, the computational analysis of CE images can help detect lesions more accurately within a shorter time. Newly introduced deep leaning-based methods have shown more remarkable results over traditional computerized approaches. A large-scale standard dataset should be prepared to develop an optimal algorithms for improving the diagnostic yield of CE. The close collaboration between information technology and medical professionals is needed. Korean Society of Gastrointestinal Endoscopy 2019-07 2019-02-21 /pmc/articles/PMC6680009/ /pubmed/30786704 http://dx.doi.org/10.5946/ce.2018.172 Text en Copyright © 2019 Korean Society of Gastrointestinal Endoscopy This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Park, Junseok Hwang, Youngbae Yoon, Ju-Hong Park, Min-Gyu Kim, Jungho Lim, Yun Jeong Chun, Hoon Jai Recent Development of Computer Vision Technology to Improve Capsule Endoscopy |
title | Recent Development of Computer Vision Technology to Improve Capsule Endoscopy |
title_full | Recent Development of Computer Vision Technology to Improve Capsule Endoscopy |
title_fullStr | Recent Development of Computer Vision Technology to Improve Capsule Endoscopy |
title_full_unstemmed | Recent Development of Computer Vision Technology to Improve Capsule Endoscopy |
title_short | Recent Development of Computer Vision Technology to Improve Capsule Endoscopy |
title_sort | recent development of computer vision technology to improve capsule endoscopy |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680009/ https://www.ncbi.nlm.nih.gov/pubmed/30786704 http://dx.doi.org/10.5946/ce.2018.172 |
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