Image Processing Techniques for Medical Mammography Masses Detection Applications

Abstract

The role of image processing is crucial in the mammography for detecting of any unwanted suspicious regions in the mammogram. Quality of image is majorly focused in proposed image enhancement technique for retrieving of efficient feature extractions. SVM and GMM based classifier models are built for improving the performance parameters of proposed methodologies. Aim of this chapter is to reduce the noise in the mammogram image in order to enhance the mammogram image. Enhancement techniques, such as, contrast stretching and histogram equalization, morphological, median filters are experimented on mammogram images and results are compared for analyzing the image enhancement. These techniques are used to improve the clarity and denoise of mammogram images. It is useful for detecting the tumors in the mammogram effectively and it is helpful to locate and size of masses or tumors accurately in mammogram. Proposed methodology shows the image from the selected range of pixels and it show the intensity of the mammogram image at the particular pixel range. By this, the mammogram image will be smoothened which will be useful for diagnosing the tumors.