Analysis of Microcalcifications Using Block Wise Local Binary Pattern and Independent component analysis in Mammograms

In India, the average age of developing a breast cancer has undergone a significant shift over last few decades. Most prominent features that indicate breast cancer are microcalcifications. Microcalcifications are tiny calcium deposits deposited on skin and non-palpable. Automatic analysis of microcalcification helps specialist in having more precise decision. The paper presents an approach that involves classification of microcalcifications into benign/malignant in mammograms. Texture features such LBP and statistical features are extracted from ROIs with microcalcification and independent component analysis is applied to reduce the feature set. These feature set is fed to artificial neural networks to classify the ROIs into malignant and benign calcifications.