Hexagonal wavelet processing of digital mammography

Laine, Andrew F.; Schuler, Sergio; Huda, Walter; Honeyman, Janice; Steinbach, Barbara

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.


Also Published In

Medical imaging 1993 : Image processing : 16-19 February 1993, Newport Beach, California ; Proceedings of SPIE, vol. 1898

More About This Work

Academic Units
Biomedical Engineering
Published Here
August 30, 2010