Please use this identifier to cite or link to this item: http://159.69.53.182:8080/xmlui/handle/123456789/465
Title: Multi-classifier method based on voting technique for mammogram image classification
Authors: Alhaj Alobeed, Mohamed
Ahmed, Ali
Osman Ibrahim, Ashraf
Keywords: Mammograms
Breast
Cancer
Breast Cancer
multi classifier voting
Multi
Classifier
Voting
early
early detection
image
classification
image classification
Issue Date: 31-Dec-2017
Publisher: JOURNAL OF SOFTWARE ENGINEERING & INTELLIGENT SYSTEMS
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
Series/Report no.: Volume 2;issue 2
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
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
URI: http://hdl.handle.net/123456789/465
ISSN: 2518-8739
Appears in Collections:Researches and Scientific Papers البحوث والأوراق العلمية

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