Denoising mammographic images using ICA

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Abstract

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 mammographic images and contribute to an accurate diagnosis. Denoising methods based on linear filters cannot preserve image structures such as edges in the same way that methods based on nonlinear filters can do it. Recently, a nonlinear denoising method based on ICA has been introduced [1,2] for natural and artificial images. The functioning of the ICA denoising method depends on the statistics of the images. In this paper, we show that mammograms have statistics appropriate for ICA denoising and we demonstrate experimentally that ICA denoising is a suitable method to remove the noise of digitised mammographys. © Springer-Verlag 2004.

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APA

Mayo, P., Escriba, F. R., & Martin, G. V. (2004). Denoising mammographic images using ICA. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3195, 1064–1071. https://doi.org/10.1007/978-3-540-30110-3_134

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