Mammography is a radiographic technique used for the detection of breast lesions. The analysis of the digital image normally requires a previous application of filters as a preprocessing step to reduce the noise level of the image, while preserving important details to carry out a suitable diagnostic. In the literature, there are a large amount of denoising techniques applied to different medical images. In this work we have studied the performance of a diffusive filter with a stopping condition based on the statistical concept of negentropy, applied to denoise mammographic images. The negentropy has been succesfully prove with other denoising methods as independent component analysis by the authors in [1]. We have evaluated the final image quality obtained, measuring a root mean squared error between the noise-free initial image and the final restored image and compared the results obtained by this diffusive filter with those obtained by an adaptative non-linear Wiener filter.