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29 June 2000 Mammogram feature analysis system using DAF wavelet
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Abstract
We present here a mammography imaging system, named DAF SparkleTM, with a particular emphasis on digital mammogram enhancement and feature analysis using interpolating Distributed Approximating Functional (DAF) wavelets, nonlinear multiscale edge enhancement, and visual group normalization technique (VGN). Sinc-type interpolating DAFs are utilized for generating a new class of biorthogonal wavelets with arbitrary smoothness in both space and frequency regions. A new nonlinear multiscale edge enhancement technique is presented here to sharpen the image edge based on the wavelet coefficients without enhancing the noise as well. The visual group normalization technique (VGN), as a natural extensions of earlier normalization techniques for noisy image restoration, is used to normalize the multiscale wavelet coefficients, remove perceptual redundancy, as well as to improve the visualization of the important diagnostic features for digital mammograms. Without prior knowledge of the `true' spatial distribution of the signal, excellent enhancement results are obtained by the present techniques.
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Haixiang Wang, Zhuoer Shi, DeSheng Zhang, Donald J. Kouri, and David K. Hoffman "Mammogram feature analysis system using DAF wavelet", Proc. SPIE 4041, Visual Information Processing IX, (29 June 2000); https://doi.org/10.1117/12.390479
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