Comparing Methods to Denoise Mammographic Images

Abstract

[EN] Digital mammographic image processing often requires a previous application of filters to reduce the noise level of the image while preserving important details. This may improve the quality of digital mamographic images and contribute to an accurate diagnosis. In the literature, one can find a large amount of denoising techniques available for different kinds of images. We have adapted some of the existing denoising algorithms to mammographic images. In this work, we compare the effect of different denoising filters acting on digitized mammograms. The considered filters are: a local Wiener filter, a wavelet filter, a filter based on independent component analysis, and finally, a filter based on the diffusion equation. The noise reduction is measured by the mean squared error