Mammography is at present one of the available method for early detection of abnormalities, which is related to breast cancer there are different lesions that are breast cancer characteristic such as masses, which can be detected through this technique. , the images are divided according to the Mini-MIAS database. In order-to classify the cluster as-malignant and benign, the 2nd order co-occurrence statistical properties of the image such as contrast, correlation, homogeneity and energy were adopted. Medical images proved to be helpful in treating and aiding diagnosing. These images are also helpful for medical student to understand their studies more properly. With the recent growth of digital imaging technologies, medical images helped medical students in their studies in terms of analysis and interpretation.

Papers:

1) S. Dehghani and M. A. Dezfooli, “Breast Cancer Diagnosis System Based on Contourlet Analysis and Support Vector Machine,” vol. 13, no. 5, pp. 1067–1076, 2011.

2) Cheng, A.; Liu, H.; Zheng, B. Computer-aided classification of mammographic masses using the deep learning technology: A preliminary study. In Proceedings of the SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, San Diego