Mammogram Breast Cancer Classification Using Gray-Level Co-Occurrence Matrix and Support Vector Machine

Breast cancer is the most common cancer in women. Breast cancer is also the deadliest cancer in women. In 2012, there were 19,750 breast cancer patients in Indonesia dead. There is no sure way to prevent breast cancer. However, the recovery rates and survival rates can be improved by early detection through routine examination. Using X-ray radiation, breast tissue can be obtained. This image is called mammogram. In this paper, a combination of Gray-level co-occurrence matrix (GLCM) and Support Vector Machine (SVM) is used to classify benign-malignant patient based on mammography image. This paper aims to find the optimal GLCM angle for breast cancer classification cases using mammogram data. Mammogram images used in this paper provided by Curated Breast Imaging Subset of Digital Database Screening Mammography (CBIS-DDSM) dataset. From experimental result, obtained accuracy 63.03% and specificity 89.01%.