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Proceedings Paper

Wavelet-morphology for mass detection in digital mammogram images
Author(s): Golshah A. Naghdy; Yue Li; Jian Wang
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Paper Abstract

In this paper, a novel wavelet-morphology method for the detection of mass abnormalities in digital mammograms is presented. The new scheme utilizes the feature extraction capability of the wavelet transform followed by a novel recursive-enhancement morphology algorithm to detect the masses. A morphology-based segmentation algorithm is finally applied to the enhanced image to separate the mass from the normal breast tissues. This technique outlines the shape of the region of interest (mass in mammograms). Tests results have confirmed the efficacy of the technique in automated detection of abnormalities in wavelet based compressed mammograms.

Paper Details

Date Published: 15 May 2003
PDF: 7 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.480109
Show Author Affiliations
Golshah A. Naghdy, Univ. of Wollongong (Australia)
Yue Li, Univ. of Wollongong (Australia)
Jian Wang, Proteome Systems, Ltd. (Australia)

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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