期刊
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
卷 34, 期 4, 页码 269-276出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compmedimag.2009.11.002
关键词
Curvelet transform; Breast cancer diagnosis; Digital mammogram; Multiresolution; Feature extraction
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. (C) 2009 Elsevier Ltd. All rights reserved.
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