Mammogram feature analysis system using DAF wavelet

Haixiang Wang; Zhuoer Shi; DeSheng Zhang; Donald J. Kouri; David K. Hoffman

doi:10.1117/12.390479

29 June 2000 Mammogram feature analysis system using DAF wavelet

Haixiang Wang, Zhuoer Shi, DeSheng Zhang, Donald J. Kouri, David K. Hoffman

Proceedings Volume 4041, Visual Information Processing IX; (2000) https://doi.org/10.1117/12.390479
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

We present here a mammography imaging system, named DAF Sparkle^TM, 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.

Citation Download Citation

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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