A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram.

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.