title: A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram.
abstract: 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.
authors.affiliation: Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak, Malaysia. tokhy2478@yahoo.com
authors.forename: Mohamed
authors.initials: M
authors.lastname: Meselhy Eltoukhy
authors.forename: Ibrahima
authors.initials: I
authors.lastname: Faye
authors.forename: Brahim
authors.initials: B
authors.lastname: Belhaouari Samir
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008327:Mammography