A survey on Barrett's esophagus analysis using machine learning

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dc.contributor.authorde Souza, Luis A. [UNESP]
dc.contributor.authorPalm, Christoph
dc.contributor.authorMendel, Robert
dc.contributor.authorHook, Christian
dc.contributor.authorEbigbo, Alanna
dc.contributor.authorProbst, Andreas
dc.contributor.authorMessmann, Helmut
dc.contributor.authorWeber, Silke [UNESP]
dc.contributor.authorPapa, João P. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionOstbayerische Technische Hochschule Regensburg (OTH Regensburg)
dc.contributor.institutionOTH Regensburg and Regensburg University
dc.contributor.institutionKlinikum Augsburg
dc.date.accessioned2018-12-11T17:36:34Z
dc.date.available2018-12-11T17:36:34Z
dc.date.issued2018-05-01
dc.description.abstractThis work presents a systematic review concerning recent studies and technologies of machine learning for Barrett's esophagus (BE) diagnosis and treatment. The use of artificial intelligence is a brand new and promising way to evaluate such disease. We compile some works published at some well-established databases, such as Science Direct, IEEEXplore, PubMed, Plos One, Multidisciplinary Digital Publishing Institute (MDPI), Association for Computing Machinery (ACM), Springer, and Hindawi Publishing Corporation. Each selected work has been analyzed to present its objective, methodology, and results. The BE progression to dysplasia or adenocarcinoma shows a complex pattern to be detected during endoscopic surveillance. Therefore, it is valuable to assist its diagnosis and automatic identification using computer analysis. The evaluation of the BE dysplasia can be performed through manual or automated segmentation through machine learning techniques. Finally, in this survey, we reviewed recent studies focused on the automatic detection of the neoplastic region for classification purposes using machine learning methods.en
dc.description.affiliationDepartment of Computing São Paulo State University UNESP
dc.description.affiliationRegensburg Medical Image Computing (ReMIC) Ostbayerische Technische Hochschule Regensburg (OTH Regensburg)
dc.description.affiliationRegensburg Center of Biomedical Engineering (RCBE) OTH Regensburg and Regensburg University
dc.description.affiliationDepartment of Otorhinolaryngology São Paulo State University
dc.description.affiliationMedizinische Klinik III Klinikum Augsburg
dc.description.affiliationUnespDepartment of Computing São Paulo State University UNESP
dc.description.affiliationUnespDepartment of Otorhinolaryngology São Paulo State University
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipCalifornia Department of Fish and Wildlife
dc.description.sponsorshipIdFAPESP: 2013/07375-0
dc.description.sponsorshipIdFAPESP: 2014/12236-1
dc.description.sponsorshipIdFAPESP: 2016/19403-6
dc.description.sponsorshipIdCNPq: 306166/2014-3
dc.description.sponsorshipIdCNPq: 307066/2017-7
dc.description.sponsorshipIdCalifornia Department of Fish and Wildlife: PA 1595/3-1
dc.format.extent203-213
dc.identifierhttp://dx.doi.org/10.1016/j.compbiomed.2018.03.014
dc.identifier.citationComputers in Biology and Medicine, v. 96, p. 203-213.
dc.identifier.doi10.1016/j.compbiomed.2018.03.014
dc.identifier.file2-s2.0-85044928254.pdf
dc.identifier.issn1879-0534
dc.identifier.issn0010-4825
dc.identifier.scopus2-s2.0-85044928254
dc.identifier.urihttp://hdl.handle.net/11449/179742
dc.language.isoeng
dc.relation.ispartofComputers in Biology and Medicine
dc.relation.ispartofsjr0,591
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectAdenocarcinoma
dc.subjectBarrett's esophagus
dc.subjectComputer-aided diagnosis
dc.subjectImage processing
dc.subjectMachine learning
dc.subjectPattern recognition
dc.titleA survey on Barrett's esophagus analysis using machine learningen
dc.typeResenha
unesp.campusUniversidade Estadual Paulista (Unesp), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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Bauru - FC - Faculdade de Ciências