Many of the women across the world suffer from breast cancer. Since the causes of this disease remain unknown, early detection and diagnosis are essential to control the breast cancer, increase the success of the treatment, save live, and reduce costs. Unfortunately, the methods proposed in the literature are suffering from low detection rates. In this paper, we proposed two new methods called C-Comp and CRoI. Both methods efficiently detect benign and malignant breast cancer tumors using shape circularity. The experimental results show that, the proposed C-Comp method achieved a detection rate of 12.3% higher than other previous work. However, the proposed CRoI method achieved a detection rate of 5.6 % higher than other previous work.
Mahdy Mohamed, Taha, A. Elmonem, Belal, & Kholeif, Sherif. (2019). Efficient Breast Cancer Classification Using Tumor Area and Boundaries Calculation. النشرة المعلوماتية في الحاسبات والمعلومات, 1(2), 1-5. doi: 10.21608/fcihib.2019.107516
MLA
Taha Mahdy Mohamed; Belal A. Elmonem; Sherif Kholeif. "Efficient Breast Cancer Classification Using Tumor Area and Boundaries Calculation". النشرة المعلوماتية في الحاسبات والمعلومات, 1, 2, 2019, 1-5. doi: 10.21608/fcihib.2019.107516
HARVARD
Mahdy Mohamed, Taha, A. Elmonem, Belal, Kholeif, Sherif. (2019). 'Efficient Breast Cancer Classification Using Tumor Area and Boundaries Calculation', النشرة المعلوماتية في الحاسبات والمعلومات, 1(2), pp. 1-5. doi: 10.21608/fcihib.2019.107516
VANCOUVER
Mahdy Mohamed, Taha, A. Elmonem, Belal, Kholeif, Sherif. Efficient Breast Cancer Classification Using Tumor Area and Boundaries Calculation. النشرة المعلوماتية في الحاسبات والمعلومات, 2019; 1(2): 1-5. doi: 10.21608/fcihib.2019.107516
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