%L scholars1247
%J Computerized Medical Imaging and Graphics
%O cited By 110
%R 10.1016/j.compmedimag.2009.11.002
%N 4
%D 2010
%K Breast cancer diagnosis; Curvelet transforms; Digital mammogram; Digital mammograms; Multi-resolutions, Face recognition; Mammography; X ray screens, Feature extraction, article; breast cancer; cancer classification; cancer diagnosis; classifier; diagnostic accuracy; diagnostic procedure; digital mammography; human; image analysis; image processing; image reconstruction; priority journal, Algorithms; Breast Neoplasms; Female; Humans; Mammography; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity
%X This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. After decomposing the mammogram images in curvelet basis, a special set of the biggest coefficients is extracted as feature vector. The Euclidean distance is then used to construct a supervised classifier. The experimental results gave a 98.59 classification accuracy rate, which indicate that curvelet transformation is a promising tool for analysis and classification of digital mammograms. © 2009 Elsevier Ltd.
%P 269-276
%A M.M. Eltoukhy
%A I. Faye
%A B.B. Samir
%V 34
%T Breast cancer diagnosis in digital mammogram using multiscale curvelet transform