Wavelet Based Segmentation Using Optimal Statistical Features on Breast Images

Elastography is the emerging imaging modality that analyzes the stiffness of the tissue for detecting and classifying breast tumors. Computer-aided detection speeds up the diagnostic process of breast cancer improving the survival rate. A multi resolution approach using Discrete wavelet transform is employed on real time images, using the low-low (LL), low-high (LH), high-low (HL), and high-high (HH) sub-bands of Daubechies family. Features are extracted, selected and then finally segmented by K-means clustering algorithm. The proposed work can be extended to Classification of the tumors.