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.