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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3JRK2U5
Repositorysid.inpe.br/sibgrapi/2015/07.13.14.11
Last Update2015:07.13.14.11.14 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2015/07.13.14.11.14
Metadata Last Update2022:05.18.22.20.58 (UTC) administrator
Citation KeyBarrosDuarSant:2015:SiClGl
TitlePathoSpotter: Um Sistema para Classificação de Glomerulopatias a partir de Imagens Histológicas Renais
FormatOn-line
Year2015
Access Date2024, Apr. 24
Number of Files1
Size358 KiB
2. Context
Author1 Barros, George Oliveira
2 Duarte, Ângelo Amâncio
3 Santos, Washington Luis Conrado dos
Affiliation1 Programa de Pós-Graduação em Computação Aplicada - Universidade Estadual de Feira de Santana
2 Programa de Pós-Graduação em Computação Aplicada - Universidade Estadual de Feira de Santana
3 Centro de Pesquisas Gonçalo Muniz - Fundação Osvaldo Cruz
EditorRios, Ricardo Araujo
Paiva, Afonso
e-Mail Addressgeogobgob@gmail.com
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador, BA, Brazil
Date26-29 Aug. 2015
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2015-07-17 18:31:15 :: geogobgob@gmail.com -> administrator :: 2015
2022-05-18 22:20:58 :: administrator -> :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordskidney histologycal images
nefropatia
image processing
computer vision
medical image analysis
AbstractThis paper describes the current state of the research and implementation of PathoSpotter-K, a classification system of glomerulopathies based on histological images from kidney. The process of identify such pathologies from images requires pathologists with great expertise in image classification, because the features of the histological images lead to a subjective analysis. Currently, the PathoSpotter-K yields classifications with 67% accuracy. Other improvements are being implemented to increase the accuracy as also as to collect more images to build a larger dataset in order to assess robustness of the system.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2015 > PathoSpotter: Um Sistema...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 13/07/2015 11:11 1.1 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3JRK2U5
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3JRK2U5
Languagept
Target Filepathospotter.pdf
User Groupadministrator
geogobgob@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPBW34M/3K24PF8
Citing Item Listsid.inpe.br/sibgrapi/2015/08.03.22.49 6
sid.inpe.br/banon/2001/03.30.15.38.24 1
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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