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One of the major causes of cancer death among middle aged women in developed countries is breast cancer. Mammography is one method used by radiologists for detection and interpretation of cancer in breast images. Over the past few years Content-based Image Retrieval (CBIR) approaches has received significant attention for medical images analysis. In this paper content based retrieval techniques were tested for tissue classification and analysis of breast images. The proposed method employs image enhancement, analysis and classification of mammograms using histogram, statistical, wavelet coefficients and spectral features. The implementation of proposed method was carried out using MATLAB software and hence can work on simple personal computer. Analysis was carried out on 56 images collected from open source mini-MIAS database. Euclidean distance was used to compare the features of query image with stored images in database. Results show that the suggested features can be used for both classification and retrieval of mammographic images. The retrieval efficiency was obtained to be 85.7%. General Terms Pattern Recognition, Medical Image Processing.

"Mammographic Image Enhancement, Classification and Retrieval using Color, Statistical and Spectral Analysis"