Computer Vision in Esophageal Cancer: A Literature Review
Main Author: | |
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Publication Date: | 2019 |
Other Authors: | , , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://hdl.handle.net/10316/101591 https://doi.org/10.1109/ACCESS.2019.2930891 |
Summary: | Esophageal cancer is a disease with a high prevalence that can be evaluated by a variety of imaging modalities, including endoscopy, computed tomography, and positron emission tomography. Computer-aided techniques could provide a valuable help in the analysis of these images, decreasing the medical work ow time and human errors. The goal of this paper is to review the existing literature on the application of computer vision techniques in the domain of esophageal cancer. After an initial phase where a set of keywords was chosen, the selected terms were used to retrieve papers from four well-known databases: Web of Science, Scopus, PubMed, and Springer. The results were scanned by merging identical entries, and eliminating the out of scope works, resulting in 47 selected papers. These were organized according to the image modality. Major results were then summarized and compared, and main shortcomings were identi ed. It could be concluded that, even though the scienti c community has already paid attention to the esophageal cancer problem, there are still several open issues. Two major ndings of this review are the nonexistence of works on MRI data and the under-exploration of recent techniques using deep learning strategies, showing the need for further investigation. |
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Computer Vision in Esophageal Cancer: A Literature ReviewComputed tomographycomputer visioncomputer aided analysisendoscopyesophageal cancerpositron emission tomographyEsophageal cancer is a disease with a high prevalence that can be evaluated by a variety of imaging modalities, including endoscopy, computed tomography, and positron emission tomography. Computer-aided techniques could provide a valuable help in the analysis of these images, decreasing the medical work ow time and human errors. The goal of this paper is to review the existing literature on the application of computer vision techniques in the domain of esophageal cancer. After an initial phase where a set of keywords was chosen, the selected terms were used to retrieve papers from four well-known databases: Web of Science, Scopus, PubMed, and Springer. The results were scanned by merging identical entries, and eliminating the out of scope works, resulting in 47 selected papers. These were organized according to the image modality. Major results were then summarized and compared, and main shortcomings were identi ed. It could be concluded that, even though the scienti c community has already paid attention to the esophageal cancer problem, there are still several open issues. Two major ndings of this review are the nonexistence of works on MRI data and the under-exploration of recent techniques using deep learning strategies, showing the need for further investigation.Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) under Project NORTE-01-0145-FEDER-0000272019info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://hdl.handle.net/10316/101591https://hdl.handle.net/10316/101591https://doi.org/10.1109/ACCESS.2019.2930891eng2169-3536Domingues, InesSampaio, Ines LucenaDuarte, HugoSantos, Joao A. M.Abreu, Pedro H.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-11T14:33:36Zoai:estudogeral.uc.pt:10316/101591Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T05:50:59.544875Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Computer Vision in Esophageal Cancer: A Literature Review |
title |
Computer Vision in Esophageal Cancer: A Literature Review |
spellingShingle |
Computer Vision in Esophageal Cancer: A Literature Review Domingues, Ines Computed tomography computer vision computer aided analysis endoscopy esophageal cancer positron emission tomography |
title_short |
Computer Vision in Esophageal Cancer: A Literature Review |
title_full |
Computer Vision in Esophageal Cancer: A Literature Review |
title_fullStr |
Computer Vision in Esophageal Cancer: A Literature Review |
title_full_unstemmed |
Computer Vision in Esophageal Cancer: A Literature Review |
title_sort |
Computer Vision in Esophageal Cancer: A Literature Review |
author |
Domingues, Ines |
author_facet |
Domingues, Ines Sampaio, Ines Lucena Duarte, Hugo Santos, Joao A. M. Abreu, Pedro H. |
author_role |
author |
author2 |
Sampaio, Ines Lucena Duarte, Hugo Santos, Joao A. M. Abreu, Pedro H. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Domingues, Ines Sampaio, Ines Lucena Duarte, Hugo Santos, Joao A. M. Abreu, Pedro H. |
dc.subject.por.fl_str_mv |
Computed tomography computer vision computer aided analysis endoscopy esophageal cancer positron emission tomography |
topic |
Computed tomography computer vision computer aided analysis endoscopy esophageal cancer positron emission tomography |
description |
Esophageal cancer is a disease with a high prevalence that can be evaluated by a variety of imaging modalities, including endoscopy, computed tomography, and positron emission tomography. Computer-aided techniques could provide a valuable help in the analysis of these images, decreasing the medical work ow time and human errors. The goal of this paper is to review the existing literature on the application of computer vision techniques in the domain of esophageal cancer. After an initial phase where a set of keywords was chosen, the selected terms were used to retrieve papers from four well-known databases: Web of Science, Scopus, PubMed, and Springer. The results were scanned by merging identical entries, and eliminating the out of scope works, resulting in 47 selected papers. These were organized according to the image modality. Major results were then summarized and compared, and main shortcomings were identi ed. It could be concluded that, even though the scienti c community has already paid attention to the esophageal cancer problem, there are still several open issues. Two major ndings of this review are the nonexistence of works on MRI data and the under-exploration of recent techniques using deep learning strategies, showing the need for further investigation. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10316/101591 https://hdl.handle.net/10316/101591 https://doi.org/10.1109/ACCESS.2019.2930891 |
url |
https://hdl.handle.net/10316/101591 https://doi.org/10.1109/ACCESS.2019.2930891 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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2169-3536 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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