Journal
COMPUTERS IN BIOLOGY AND MEDICINE
Volume 38, Issue 10, Pages 1045-1055Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2008.07.006
Keywords
Mammography image enhancement; Preprocessing; Microcalcification detection; CAD
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In this work. the effect of an image enhancement processing stage and the parameter tuning of a computer-aided detection (CAD) system for the detection of microcalcifications in mammograms is assessed. Five (5) image enhancement algorithms were tested introducing the contrast-limited adaptive histogram equalization (CLAHE), the local range modification (LRM) and the redundant discrete wavelet (RDW) linear stretching and shrinkage algorithms. CAD tuning optimization was targeted to the percentage of the most contrasted pixels and the size of the minimum detectable object which could satisfactorily represent a microcalcification. The highest performance in two mammographic datasets, were achieved for LRM (A(Z) = 0.932) and the wavelet-based linear stretching (AZ = 0.926) methodology. (C) 2008 Elsevier Ltd. All rights reserved.
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