Breast Cancer Diagnosis Based on Texture Feature Extraction Using Curvelet Transform

This paper proposes a method for breast cancer
diagnosis in digital mammogram. The article focuses on using
texture analysis based on curvelet transform for the classification
of tissues. The most discriminative texture features of regions of
interest are extracted and then, a classifier is built. The approach
consists of three steps, detecting the abnormality, classify this
abnormality into one of the abnormality types and lastly
distinguish between benign and malignant tumors.