Computer Aided Diagnosis System for Breast Cancer using ID3 and SVM Based on Slantlet Transform

Mohammed Salih Mahdi

doi:10.25212/lfu.qzj.2.2.16

توێژەران

Mohammed Salih Mahdi BIT, Business information College, University of Information Technology and Communications- Iraq

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https://doi.org/10.25212/lfu.qzj.2.2.16

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Breast cancer, CAD, Slantlet, ID3, SVM

پوختە

Lately, the woman's chest cancer is the 2nd reason of deaths in females. Mam.mog.ram images are medical images, which can be read by physicians to detect breast carcinomas. In this paper, proposed Computer Aided Diagnosis system that can assist the doctors in hospitals to improve the diagnosis of the disease to detect cancer cells. Enhance the undesirable effects the of mam.mog.ram images by using slantlet transformer , set of different stages and classifies as normal, abnormal according to ID3 and SVM. For the same testing set, the practical outcomes displays SVM classifier with an accuracy of 95% and ID3 classifier with an accuracy of 92% based on MIAS database.

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سەرچاوەکان

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