Classification Of MRI Brain Tumor and Mammogram Images Using Learning Vector Quantization Neural Network

A proper and accurate classification technique with detection of brain tumor has been presented and proposed. The system uses neural network based approach for brain and breast image classification. Now a day's Magnetic resonance imaging (MRI technique is used for early detection of any abnormal changes in tissues and organs. The projected method is evaluated on two distinct databases i.e. Clinical database is database of brain MRI and one more Standard Digital Database for Screening Mammography (DDSM). The proposed system consists of Preprocessing using image normalization, morphological operations using erosion, dilation and Anisotropic Diffusion Filter (ADF), Extraction of texture feature using gray level co-occurrence matrix (GLCM) and classification into normal and abnormal using machine learning algorithm and quantization techniques i.e. LVQ. The proposed system achieved the accuracy of 68.85% for DDSM mammography database and 79.35% on clinical brain MRI database