Detection of microcalcifications in mammograms using local maxima and adaptive wavelet transform analysis

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Detection_of_microcalcifications_in_mammograms_using_local_maxima_and_adaptive_wavelet_transform_analysis.pdf (273.75 KB)

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2002-10-24

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Abstract

A method for computer-aided diagnosis of microcalcification clusters in mammogram images is presented. Microcalcification clusters which are an early sign of breast cancer appear as isolated bright spots in mammograms. Therefore they correspond to local maxima of the image. The local maxima of the image is first detected and they are ranked according to a higher-order statistical test performed over the subband domain data.

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Electronics Letters

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The Institution of Engineering and Technology
(IET)

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Mammography, Medical image processing, Wavelet transforms, Least mean squares methods, Higher order statistics, Microcalcification clusters, Computer-aided diagnosis, Mammogram images, Breast cancer, Isolated bright spots, Higher-order statistical test, Subband domain data, Adaptive wavelet transform analysis, Local maxima, Least mean square algorithm, Filterbank structure

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http://hdl.handle.net/11693/48701

Published Version (Please cite this version)

http://dx.doi.org/10.1049/el:20020907

Collections

Scholarly Publications - Electrical and Electronics Engineering

Language

English

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Article