Segmentation and Classification of Breast Cancer Tumour

Abstract

Breast cancer is cancer that forms in the cells of the breasts. Breast cancer is the most common cancer diagnosed in women in the world. Breast cancer can occur in both men and women, but it's far more common in women. Early detection of breast cancer tumours is crucial in the treatment. In this study, we presented a computer aided diagnosis expectation maximization segmentation and co-occurrence texture features from wavelet approximation tumour image of each slice and evaluated the performance of SVM Algorithm. We tested the model on 50 patients, among them, 25 are benign and 25 malign. The 80% of the images are allocated for training and 20% of images reserved for testing. The proposed model classified 2 patients correctly with success rate of 80% in case of 5 Fold Cross-Validation 
 Keywords: Breast Cancer, Computer-Aided Diagnosis (CAD), Magnetic Resonance Imaging (MRI);

Intelligent Mobile Models and Their Application in the Educational Process

“…The use of information and communication technologies in education is formulated with the reasonable introduction of new technologies that adapt the educational process to effective learning [3][4][5]. The development of information and communication technologies also requires a timely change in the system of evaluation and use of knowledge.…”