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Proceedings Paper

Hexagonal wavelet processing of digital mammography
Author(s): Andrew F. Laine; Sergio Schuler; Walter Huda; Janice C. Honeyman-Buck; Barbara G. Steinbach
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Paper Abstract

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms and used to enhance features of importance to mammography within a continuum of scale-space. We present a method of contrast enhancement based on an overcomplete, non-separable multiscale representation: the hexagonal wavelet transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by local and global non-linear operators. Multiscale edges identified within distinct levels of transform space provide local support for enhancement. We demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

Paper Details

Date Published: 14 September 1993
PDF: 15 pages
Proc. SPIE 1898, Medical Imaging 1993: Image Processing, (14 September 1993); doi: 10.1117/12.154543
Show Author Affiliations
Andrew F. Laine, Univ. of Florida (United States)
Sergio Schuler, Univ. of Florida (United States)
Walter Huda, Univ. of Florida (United States)
Janice C. Honeyman-Buck, Univ. of Florida (United States)
Barbara G. Steinbach, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 1898:
Medical Imaging 1993: Image Processing
Murray H. Loew, Editor(s)

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