Breast cancer diagnosis in digital mammogram using multiscale curvelet transform

M.M., Eltoukhy and I., Faye and B.B., Samir (2010) Breast cancer diagnosis in digital mammogram using multiscale curvelet transform. Computerized Medical Imaging and Graphics. ISSN 8956111

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Abstract

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. All rights reserved.

Item Type: Article
Uncontrolled Keywords: Breast cancer diagnosis; Curvelet transform; Digital mammogram; Feature extraction; Multiresolution
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE: Centre of Excellence > Center for Intelligent Signal and Imaging Research
Departments > Electrical & Electronic Engineering
Departments > Fundamental & Applied Sciences
Research Institutes > Institute for Health Analytics
Depositing User: Dr Ibrahima Faye
Date Deposited: 09 Mar 2010 01:07
Last Modified: 19 Jan 2017 08:24
URI: http://scholars.utp.edu.my/id/eprint/388

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