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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PJ5TCS
Repositorysid.inpe.br/sibgrapi/2017/09.04.22.16
Last Update2017:09.04.22.16.45 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/09.04.22.16.45
Metadata Last Update2022:05.18.22.18.24 (UTC) administrator
Citation KeyAndradePaivSilv:2017:AnImTe
TitleAnálise de Imagens de Termografia Dinâmica para Classificação de Alterações na Mama Usando Séries Temporais
FormatOn-line
Year2017
Access Date2024, May 02
Number of Files1
Size436 KiB
2. Context
Author1 Andrade, Felipe Jordão Pinheiro de
2 Paiva, Anselmo Cardoso
3 Silva, Aristófanes Corrêa
Affiliation1 Universidade Federal do Maranhão
2 Universidade Federal do Maranhão
3 Universidade Federal do Maranhão
EditorTorchelsen, 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 Addressfelipejordaopinheiro@gmail.com
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeUndergraduate Work
History (UTC)2017-09-04 22:16:45 :: felipejordaopinheiro@gmail.com -> administrator ::
2022-05-18 22:18:24 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsTermografia Dinâmica
Séries Temporais
AbstractWith the increase in the number of cases of breast cancer in the last years, the need for auxiliary techniques for the detection of the disease is evident. Dynamic thermography can be used as an auxiliary method to the gold standard, the mammography screening. The thermography exam takes advantage of the fact that the lesions present a higher temperature than the healthy neighboring tissues. In this work, we propose a methodology for the transformation of thermal signals into time series, from which features for the classification task will be extracted. In the paper we compare the K-Star and Support Vector Machine classifiers with results of 95.8% accuracy, 93.6% sensitivity and 95.9% specificity.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2017 > Análise de Imagens...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 04/09/2017 19:16 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PJ5TCS
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PJ5TCS
Languagept
Target FileCameraReady_Sibigrapi_termica.pdf
User Groupfelipejordaopinheiro@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 8
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi 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 versiontype volume


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