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Published Articles >> Table of Contents >> Abstract
Computer Graphics and Image Processing, XVII Brazilian Symposium on (SIBGRAPI'04)
pp. 2-9
An Adaptive Approach to Mammographic Image Denoising and Enhancement
Jacob Scharcanski, UFRGS - Universidade Federal do Rio Grande do Sul, Brasil
Claudio Rosito Jung, UNISINOS - Universidade do Vale do Rio dos Sinos, Brasil
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SIBGRA.2004.1352936
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| Abstract |
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This paper describes a new method for mammographic image noise suppression and enhancement based on the wavelet transform. At each resolution, coefficients associated with noise are modelled by Gaussian random variables; coefficients associated with edges are modelled by Generalized Gaussian random variables, and a shrinkage function is assembled based on posterior probabilities. The shrinkage functions at consecutive scales are combined, and then applied to the wavelets coefficients. Given a resolution of analysis, the image denoising process is adaptive (i.e. do not require further parameter adjustments), and the selection of a gain factor provides the desired detail enhancement. The enhancement function was designed to avoid introducing artifacts in the enhancement process, which is essential in mammographic image analysis. Our preliminary results indicate that our method allows to detect microcalcifications and other suspicious structures in situations where their detection would be difficult otherwise. Compared to other approaches, our method requires less parameter adjustments by the user.
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 Additional Information
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Index Terms- mammography, image denoising, image enhancement, multiresolution analysis, wavelets
Citation:
Jacob Scharcanski, Claudio Rosito Jung,
"An Adaptive Approach to Mammographic Image Denoising and Enhancement,"
sibgrapi,
pp. 2-9,
Computer Graphics and Image Processing, XVII Brazilian Symposium on (SIBGRAPI'04),
2004
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