Journal
COMPUTERS IN BIOLOGY AND MEDICINE
Volume 40, Issue 4, Pages 384-391Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2010.02.002
Keywords
Wavelet; Curvelet; Breast cancer; Digital mammogram; Multiresolution; Feature extraction
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This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram. Using multiresolution analysis, mammogram images are decomposed into different resolution levels, which are sensitive to different frequency bands. A set of the biggest coefficients from each decomposition level is extracted. Then a supervised classifier system based on Euclidian distance is constructed. The performance of the classifier is evaluated using a 2 x 5-fold cross validation followed by a statistical analysis. The experimental results suggest that curvelet transform outperforms wavelet transform and the difference is statistically significant. (C) 2010 Elsevier Ltd. All rights reserved.
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