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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,...

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Detalles Bibliográficos
Autores principales: Park, Junseok, Hwang, Youngbae, Yoon, Ju-Hong, Park, Min-Gyu, Kim, Jungho, Lim, Yun Jeong, Chun, Hoon Jai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Gastrointestinal Endoscopy 2019
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.
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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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