Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method

Faye, Ibrahima and Brahim Belhaouari , Samir and Eltoukhy, Mohamed M. M. (2009) Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method. In: International Conference Computer and Electrical Engineering.

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Abstract

This paper introduces a new method of feature
extraction from Wavelet coefficients for classification of digital
mammograms. A matrix is constructed by putting Wavelet
coefficients of each image of a building set as a row vector. The
method consists then on selecting by threshold, the columns
which will maximize the Euclidian distances between the
different class representatives. The selected columns are then
used as features for classification. The method is tested using a
set of images provided by the Mammographic Image Analysis
Society (MIAS) to classify between normal and abnormal and
then between benign and malignant tissues. For both
classifications, a high accuracy rate (98%) is achieved.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE: Centre of Excellence > Center for Intelligent Signal and Imaging Research
Departments > Fundamental & Applied Sciences
Depositing User: Dr Ibrahima Faye
Date Deposited: 14 Aug 2012 03:09
Last Modified: 19 Jan 2017 08:25
URI: http://scholars.utp.edu.my/id/eprint/7872

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