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Proceedings Paper

Morphological filtering and multiresolution fusion for mammographic microcalcification detection
Author(s): Lulin Chen; Chang Wen Chen; Kevin J. Parker
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Paper Abstract

Mammographic images are often of relatively low contrast and poor sharpness with non-stationary background or clutter and are usually corrupted by noise. In this paper, we propose a new method for microcalcification detection using gray scale morphological filtering followed by multiresolution fusion and present a unified general filtering form called the local operating transformation for whitening filtering and adaptive thresholding. The gray scale morphological filters are used to remove all large areas that are considered as non-stationary background or clutter variations, i.e., to prewhiten images. The multiresolution fusion decision is based on matched filter theory. In addition to the normal matched filter, the Laplacian matched filter which is directly related through the wavelet transforms to multiresolution analysis is exploited for microcalcification feature detection. At the multiresolution fusion stage, the region growing techniques are used in each resolution level. The parent-child relations between resolution levels are adopted to make final detection decision. FROC is computed from test on the Nijmegen database.

Paper Details

Date Published: 25 April 1997
PDF: 12 pages
Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); doi: 10.1117/12.274183
Show Author Affiliations
Lulin Chen, Univ. of Rochester (United States)
Chang Wen Chen, Univ. of Missouri (United States)
Kevin J. Parker, Univ. of Rochester (United States)

Published in SPIE Proceedings Vol. 3034:
Medical Imaging 1997: Image Processing
Kenneth M. Hanson, Editor(s)

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