| Summary: | Computer Aided Diagnosis (CAD) system plays an important role in the medical field. It helps to reduce the mortality rate due to the early diagnosis of cancers. Photographing the changes in the internal breast structure due to the formation of masses and MicroCalcifications (MC) for the detection of breast cancer is known as mammography. It uses X-rays to capture the breast tissues. In this paper, the breast tumour in the mammogram is classified into benign or malignant classes using surfacelet transform. First, the Region Of Interest (ROI) is extracted and then enhanced using histogram equalization. The enhanced mammogram ROI is subjected to surfacelet transform and features are extracted using surfacelet coefficients. Then the features are fed to Decision Tree (DT) classifier for two class prediction; benign or malignant.
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