Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/52926
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Freitas, Nuno R. | por |
dc.contributor.author | Vieira, Pedro Miguel | por |
dc.contributor.author | Lima, Estêvão Augusto Rodrigues de | por |
dc.contributor.author | Lima, C. S. | por |
dc.date.accessioned | 2018-03-20T12:29:20Z | - |
dc.date.issued | 2017-09-13 | - |
dc.identifier.isbn | 978-1-5090-2809-2 | por |
dc.identifier.issn | 1557-170X | - |
dc.identifier.uri | https://hdl.handle.net/1822/52926 | - |
dc.description.abstract | Nowadays the diagnosis of bladder lesions relies upon cystoscopy examination and depends on the interpreter's experience. State of the art of bladder tumor identification are based on 3D reconstruction, using CT images (Virtual Cystoscopy) or images where the structures are exalted with the use of pigmentation, but none uses white light cystoscopy images. An initial attempt to automatically identify tumoral tissue was already developed by the authors and this paper will develop this idea. Traditional cystoscopy images processing has a huge potential to improve early tumor detection and allows a more effective treatment. In this paper is described a multivariate approach to do segmentation of bladder cystoscopy images, that will be used to automatically detect and improve physician diagnose. Each region can be assumed as a normal distribution with specific parameters, leading to the assumption that the distribution of intensities is a Gaussian Mixture Model (GMM). Region of high grade and low grade tumors, usually appears with higher intensity than normal regions. This paper proposes a Maximum a Posteriori (MAP) approach based on pixel intensities read simultaneously in different color channels from RGB, HSV and CIELab color spaces. The Expectation-Maximization (EM) algorithm is used to estimate the best multivariate GMM parameters. Experimental results show that the proposed method does bladder tumor segmentation into two classes in a more efficient way in RGB even in cases where the tumor shape is not well defined. Results also show that the elimination of component L from CIELab color space does not allow definition of the tumor shape. | por |
dc.description.sponsorship | This work is supported by FCT with the reference project UID/EEA/04436/2013, by FEDER funds through the COMPETE 2020 – Programa Operacional Competitividade e Internacionalização (POCI) with the reference project POCI-01-0145-FEDER-006941 and with the grant SFRH/BD/92143/2013. | por |
dc.language.iso | eng | por |
dc.publisher | IEEE | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147325/PT | por |
dc.rights | restrictedAccess | por |
dc.title | Using cystoscopy to segment bladder tumors with a multivariate approach in different color spaces | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
oaire.citationConferenceDate | 11 - 15 July 2017 | por |
sdum.event.title | EMBC'17 - 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society | por |
sdum.event.type | conference | por |
oaire.citationStartPage | 656 | por |
oaire.citationEndPage | 659 | por |
oaire.citationConferencePlace | Jeju Island, Korea | por |
dc.date.updated | 2018-03-12T15:12:20Z | - |
dc.identifier.doi | 10.1109/EMBC.2017.8036910 | por |
dc.identifier.pmid | 29059958 | por |
dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | por |
dc.subject.wos | Science & Technology | por |
sdum.export.identifier | 4387 | - |
sdum.journal | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | - |
sdum.conferencePublication | 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) | por |
Aparece nas coleções: | DEI - Artigos em atas de congressos internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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08036910.pdf Acesso restrito! | 843,02 kB | Adobe PDF | Ver/Abrir |