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Comparison of a dyadic wavelet image enhancement algorithm with unsharp masking and median filtering for mammography

Abstract

Image processing techniques using wavelet signal analysis techniques have shown promise in mammography. Wavelet algorithms are compared with traditional image enhancement techniques of unsharp masking and median filtering. Computer simulated phantom images were generated containing lesions mimicking masses and microcalcifications. The degree of image enhancement was evaluated by comparing processed and original signal-to-noise (SNR) ratios in such phantom images. Results obtained in this study suggest that image processing algorithms based on the wavelet transform are likely to enhance the visibility of low-contrast features in mammograms

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