Improving the mammogram images by intelligibility mammogram enhancement method

Image enhancement plays a key role in mammography for better analysis of breast cancer detection. Poor quality of mammogram images may produce ambiguous assumptions about the results in breast cancer predictions. Existing image enhancement methods such as median filter, morphological method, wavelet transformation, contrast stretching are produced better quality of images, however, they cannot accentuates the image features includes boundaries and edges. In mammography, it is required to accentuate the boundary and edges features with good quality. Therefore, this paper proposed the work for intelligibility of these boundary and edges features, known as intelligibility mammogram enhancement method (IMEM). Demonstration of efficiency of proposed method and comparative results are presented in the experimental study using mammogram image datasets.