1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPAW/3PF8RQE |
Repository | sid.inpe.br/sibgrapi/2017/08.18.03.29 |
Last Update | 2017:08.18.03.29.56 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2017/08.18.03.29.56 |
Metadata Last Update | 2022:06.14.00.08.45 (UTC) administrator |
DOI | 10.1109/SIBGRAPI.2017.47 |
Citation Key | JúniorAfonPalmPapa:2017:BaEsId |
Title | Barrett’s Esophagus Identification Using Optimum-Path Forest |
Format | On-line |
Year | 2017 |
Access Date | 2024, Oct. 15 |
Number of Files | 1 |
Size | 404 KiB |
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2. Context | |
Author | 1 Júnior, Luis Antonio de Souza 2 Afonso, Luis Cláudio Sugi 3 Palm, Christoph 4 Papa, João Paulo |
Affiliation | 1 Federal University of São Carlos - UFScar 2 Federal University of São Carlos - UFScar 3 Ostbayerische Technische Hochschule Regensburg 4 São Paulo State University - UNESP |
Editor | Torchelsen, Rafael Piccin Nascimento, Erickson Rangel do Panozzo, Daniele Liu, Zicheng Farias, Mylène Viera, Thales Sacht, Leonardo Ferreira, Nivan Comba, João Luiz Dihl Hirata, Nina Schiavon Porto, Marcelo Vital, Creto Pagot, Christian Azambuja Petronetto, Fabiano Clua, Esteban Cardeal, Flávio |
e-Mail Address | luis.souza@dc.ufscar.br |
Conference Name | Conference on Graphics, Patterns and Images, 30 (SIBGRAPI) |
Conference Location | Niterói, RJ, Brazil |
Date | 17-20 Oct. 2017 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2017-08-18 03:29:56 :: luis.souza@dc.ufscar.br -> administrator :: 2022-06-14 00:08:45 :: administrator -> :: 2017 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | barrett's esophagus machine learning pattern recognition |
Abstract | Computer-assisted analysis of endoscopic images can be helpful to the automatic diagnosis and classification of neoplastic lesions. Barretts esophagus (BE) is a common type of reflux that is not straightforward to be detected by endoscopic surveillance, thus being way susceptible to erroneous diagnosis, which can cause cancer when not treated properly. In this work, we introduce the Optimum-Path Forest (OPF) classifier to the task of automatic identification of Barretts esophagus, with promising results and outperforming the wellknown Support Vector Machines (SVM) in the aforementioned context. We consider describing endoscopic images by means of feature extractors based on key point information, such as the Speeded up Robust Features (SURF) and Scale-Invariant Feature Transform (SIFT), for further designing a bag-of-visual-words that is used to feed both OPF and SVM classifiers. The best results were obtained by means of the OPF classifier for both feature extractors, with values lying on 0.732 (SURF) - 0.735 (SIFT) for sensitivity, 0.782 (SURF) - 0.806 (SIFT) for specificity, and 0.738 (SURF) - 0.732 (SIFT) for the accuracy. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2017 > Barrett’s Esophagus Identification... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Barrett’s Esophagus Identification... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/8JMKD3MGPAW/3PF8RQE |
zipped data URL | http://urlib.net/zip/8JMKD3MGPAW/3PF8RQE |
Language | en |
Target File | PID4956031.pdf |
User Group | luis.souza@dc.ufscar.br |
Visibility | shown |
Update Permission | not transferred |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPAW/3PKCC58 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2017/09.12.13.04 31 sid.inpe.br/sibgrapi/2022/06.10.21.49 2 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume |
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