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DC Field | Value | Language |
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dc.contributor.author | Alhaj Alobeed, Mohamed | - |
dc.contributor.author | Ahmed, Ali | - |
dc.contributor.author | Osman Ibrahim, Ashraf | - |
dc.date.accessioned | 2018-08-11T12:23:11Z | - |
dc.date.available | 2018-08-11T12:23:11Z | - |
dc.date.issued | 2017-12-31 | - |
dc.identifier.citation | Mohemd, 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.org | en_US |
dc.identifier.issn | 2518-8739 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/465 | - |
dc.description | Breast 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 ones | en_US |
dc.description.abstract | Breast 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 ones | en_US |
dc.description.sponsorship | Shendi University | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | JOURNAL OF SOFTWARE ENGINEERING & INTELLIGENT SYSTEMS | en_US |
dc.relation.ispartofseries | Volume 2;issue 2 | - |
dc.subject | Mammograms | en_US |
dc.subject | Breast | en_US |
dc.subject | Cancer | en_US |
dc.subject | Breast Cancer | en_US |
dc.subject | multi classifier voting | en_US |
dc.subject | Multi | en_US |
dc.subject | Classifier | en_US |
dc.subject | Voting | en_US |
dc.subject | early | en_US |
dc.subject | early detection | en_US |
dc.subject | image | en_US |
dc.subject | classification | en_US |
dc.subject | image classification | en_US |
dc.title | Multi-classifier method based on voting technique for mammogram image classification | en_US |
dc.type | Article | en_US |
Appears in Collections: | Researches and Scientific Papers البحوث والأوراق العلمية |
Files in This Item:
File | Description | Size | Format | |
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Multiclassifier_method_based_on_voting_technique_for_mammogrm_image_classification.pdf | 544.94 kB | Adobe PDF | View/Open |
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