A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis of mammogram classification using a wavelet transform decomposition
Pattern Recognition Letters - Special issue: Sibgrapi 2001
Multiresolution mammogram analysis in multilevel decomposition
Pattern Recognition Letters
Wavelet and curvelet moments for image classification: Application to aggregate mixture grading
Pattern Recognition Letters
Computers in Biology and Medicine
Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural
Expert Systems with Applications: An International Journal
Multiresolution detection of spiculated lesions in digital mammograms
IEEE Transactions on Image Processing
Contourlet-based mammography mass classification
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Computers in Biology and Medicine
Fully automated gradient based breast boundary detection for digitized X-ray mammograms
Computers in Biology and Medicine
A fuzzy rule-based approach for characterization of mammogram masses into BI-RADS shape categories
Computers in Biology and Medicine
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
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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 2x5-fold cross validation followed by a statistical analysis. The experimental results suggest that curvelet transform outperforms wavelet transform and the difference is statistically significant.