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Using curvelet transform to detect breast cancer in digital mammogram

Faye , I. and Eltoukhy , M.M. and B.Belhaouari, S. (2009) Using curvelet transform to detect breast cancer in digital mammogram. In: 2009 5th International Colloquium on Signal Processing and Its Applications, CSPA 2009, 6 March 2009 through 8 March 2009, Kuala Lumpur.

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Abstract

This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. The motivation of this approach is the desire of using the advantages of curvelet transform into mammogram analysis. Curvelet provide stable, efficient and near-optimal representation of otherwise smooth objects having discontinuities along smooth curves. Since medical images have several objects and curved shaped, it is expected that the curvelet transform would be better for classification of cancer classes in digital mammogram. To construct and evaluate a supervised classifier for this problem, by transforming the data of the images in curvelet basis and then using a special set of coefficients as the features tailored towards separating each of those classes. The experimental results indicate that using curvelet transform significantly improves the classification of cancer classes. ©2009 IEEE.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Breast Cancer; Breast cancer diagnosis; Curvelet transforms; Curvelets; Digital mammograms; Medical images; Near-optimal representations; Smooth curves; Supervised classifiers; Mammography; Signal processing; X ray screens; Object recognition
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE:Departments > Fundamental & Applied Sciences
ID Code:1729
Deposited By: Dr Ibrahima Faye
Deposited On:26 Apr 2010 08:36
Last Modified:19 Jan 2017 08:25

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