Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/26855
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dc.contributor.authorAhamad, NamaregMohamad Ibrahim-
dc.contributor.authorSupervisor, -YasirAbdalgedirMohamadHamid-
dc.date.accessioned2021-12-07T07:50:10Z-
dc.date.available2021-12-07T07:50:10Z-
dc.date.issued2021-03-30-
dc.identifier.citationAhamad, NamaregMohamad Ibrahim . Enhancement of MammogramImagesClassification Accuracy using Decision Tree Algorithm \ NamaregMohamad Ibrahim Ahamad ; YasirAbdalgedirMohamadHamid .- Khartoum: Sudan University of Science and Technology, College of Computer Science and Information Technology, 2021 .- 63p. :ill. ;28cm .- M.Scen_US
dc.identifier.urihttp://repository.sustech.edu/handle/123456789/26855-
dc.descriptionThesisen_US
dc.description.abstractBreast cancer is the disease that most common malignancy affects female. It has been considered as a second most common leading cause of cancer death among other type of cancer, specifically in developing countries.Most of the previous researches in mammogram images achieved low classification accuracy that because of either inaccurate features or improper classifier methods.The aim of this research is to enhance the classification accuracy in mammogram images using decision tree algorithm. The study methodology emphasis of six phases starting by collecting images, preprocessing (image cropping of region of interest), features extracting, feature selection, classification and end with testing and evaluating. The experimental results using mammogram image analysis society (MIAS) Dataset showed that this approach achieves accuracy of 87.47.en_US
dc.description.sponsorshipSudan University of Science & Technologyen_US
dc.language.isoenen_US
dc.publisherSudan University of Science and Technologyen_US
dc.subjectComputer Science and Information Technologyen_US
dc.subjectEnhancement of Mammogramen_US
dc.subjectImages Classification Accuracyen_US
dc.subjectDecision Tree Algorithmen_US
dc.titleEnhancement of MammogramImagesClassification Accuracy using Decision Tree Algorithmen_US
dc.title.alternativeتعزيز دقة تصنيف صور الماموقرام بإستخدام خوارزمية شجرة القرارen_US
dc.typeThesisen_US
Appears in Collections:Masters Dissertations : Computer Science and Information Technology

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