Adaptive mammographic image feature enhancement using wavelet-based multiresolution analysis

Lulin Chen; Chang Wen Chen; Kevin J. Parker

doi:10.1117/12.236013

22 March 1996 Adaptive mammographic image feature enhancement using wavelet-based multiresolution analysis

Lulin Chen, Chang Wen Chen, Kevin J. Parker

Proceedings Volume 2762, Wavelet Applications III; (1996) https://doi.org/10.1117/12.236013
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

This paper presents a novel and computationally efficient approach to an adaptive mammographic image feature enhancement using wavelet-based multiresolution analysis. Upon wavelet decomposition applied to a given mammographic image, we integrate the information of the tree-structured zerocrossings of wavelet coefficients and the information of the low-pass filtered subimage to enhance the desired image features. A discrete wavelet transform with pyramidal structure has been employed to speed up the computation for wavelet decomposition and reconstruction. The spatio-frequency localization property of the wavelet transform is exploited based on the spatial coherence of image and the principle of human psychovisual mechanism. Preliminary results show that the proposed approach is able to adaptively enhance local edge features, suppress noise, and improve global visualization of mammographic image features. This wavelet-based multiresolution analysis is therefore promising for computerized mass screening of mammograms.

Citation Download Citation

Lulin Chen, Chang Wen Chen, and Kevin J. Parker "Adaptive mammographic image feature enhancement using wavelet-based multiresolution analysis", Proc. SPIE 2762, Wavelet Applications III, (22 March 1996); https://doi.org/10.1117/12.236013

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