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AuthorPeyret R.
AuthorKhelifi F.
AuthorBouridane A.
AuthorAl-Maadeed, Somaya
Available date2022-05-19T10:23:12Z
Publication Date2017
Publication NameBioSMART 2017 - Proceedings: 2nd International Conference on Bio-Engineering for Smart Technologies
ResourceScopus
Identifierhttp://dx.doi.org/10.1109/BIOSMART.2017.8095322
URIhttp://hdl.handle.net/10576/31133
AbstractCancer is classified by the World Health Organisation as a worldwide problem and its effect is increasing. A timely diagnosis is crucial and an early detection can be vital leading to an effective diagnosis. This paper proposes an automated classification system of prostate cancer using multispectral imagery for an early detection. It revolves around a block based texture analysis that uses multiscale multispectral local binary pattern texture features combined with a bagging ensemble method and codebooks. Extensive experiments have been carried out using a real dataset and the result obtained show an accuracy of 96.0%. The findings were also analysed and compared against a few existing and similar techniques and the results suggest that the proposed approach is attractive.
Sponsor*This work is supported by the Qatar National Research Fund through National Priority Research Program (NPRP) No 6-249-1-053. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the Qatar National Research Fund or Qatar University.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectBins
Urology
Automated classification systems
Automatic diagnosis
Ensemble methods
Local binary patterns
Multi-spectral imagery
Prostate cancers
Texture analysis
Texture features
Diseases
TitleAutomatic diagnosis of prostate cancer using multispectral based linear binary pattern bagged codebooks
TypeConference Paper
dc.accessType Abstract Only


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