Please use this identifier to cite or link to this item: http://repository.ush.edu.sd:8080/xmlui/handle/123456789/465
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dc.contributor.authorAlhaj Alobeed, Mohamed-
dc.contributor.authorAhmed, Ali-
dc.contributor.authorOsman Ibrahim, Ashraf-
dc.date.accessioned2018-08-11T12:23:11Z-
dc.date.available2018-08-11T12:23:11Z-
dc.date.issued2017-12-31-
dc.identifier.citationMohemd, Alhaj Alobeed & et al, JOURNAL OF SOFTWARE ENGINEERING & INTELLIGENT SYSTEMS, ISSN 2518-8739 31st December 2017, Volume 2, Issue 3, JSEIS, CAOMEI Copyright © 2016-2017 www.jseis.orgen_US
dc.identifier.issn2518-8739-
dc.identifier.urihttp://hdl.handle.net/123456789/465-
dc.descriptionBreast cancer is the disease most common malignancy affects female population and the number of affected people is the second most common leading cause of cancer deaths among all cancer types in the developing countries. Nowadays, there is no sure way to prevent breast cancer, because its cause is not yet fully known. But there are some ways that might lower risk such as early detection of breast cancer can play an important role in reducing the associated morbidity and mortality rates. The basic idea of this paper is to a propose classification method based on multiclassifier voting method that can aid the physician in a mammogram image classification. The study emphasis of five phases starting in collect images, pre-processing (image cropping of ROI), features extracting, classification and end with testing and evaluating. The experimental results show that the voting achieves accuracy of87.50 % which is a good classification result compared to individual onesen_US
dc.description.abstractBreast cancer is the disease most common malignancy affects female population and the number of affected people is the second most common leading cause of cancer deaths among all cancer types in the developing countries. Nowadays, there is no sure way to prevent breast cancer, because its cause is not yet fully known. But there are some ways that might lower risk such as early detection of breast cancer can play an important role in reducing the associated morbidity and mortality rates. The basic idea of this paper is to a propose classification method based on multiclassifier voting method that can aid the physician in a mammogram image classification. The study emphasis of five phases starting in collect images, pre-processing (image cropping of ROI), features extracting, classification and end with testing and evaluating. The experimental results show that the voting achieves accuracy of87.50 % which is a good classification result compared to individual onesen_US
dc.description.sponsorshipShendi Universityen_US
dc.language.isoen_USen_US
dc.publisherJOURNAL OF SOFTWARE ENGINEERING & INTELLIGENT SYSTEMSen_US
dc.relation.ispartofseriesVolume 2;issue 2-
dc.subjectMammogramsen_US
dc.subjectBreasten_US
dc.subjectCanceren_US
dc.subjectBreast Canceren_US
dc.subjectmulti classifier votingen_US
dc.subjectMultien_US
dc.subjectClassifieren_US
dc.subjectVotingen_US
dc.subjectearlyen_US
dc.subjectearly detectionen_US
dc.subjectimageen_US
dc.subjectclassificationen_US
dc.subjectimage classificationen_US
dc.titleMulti-classifier method based on voting technique for mammogram image classificationen_US
dc.typeArticleen_US
Appears in Collections:Researches and Scientific Papers البحوث والأوراق العلمية

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