Curvelet based feature extraction method for breast cancer diagnosis in digital mammogram

Mohamed Meselhy Eltoukhy, Ibrahima Faye, Brahim Belhaouari Samir

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Citations (Scopus)

Abstract

This paper proposes a method for breast cancer diagnosis in digital mammogram. The article focuses on using texture analysis based on curvelet transform for the classification of tissues. The most discriminative texture features of regions of interest are extracted. Then, a nearest neighbor classifier based on Euclidian distance is constructed. The obtained results calculated using 5-fold cross validation. The approach consists of two steps, detecting the abnormalities and then classifies the abnormalities into benign and malignant tumors.

Original languageEnglish
Title of host publication2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010 - Kuala Lumpur, Malaysia
Duration: 15 Jun 201017 Jun 2010

Publication series

Name2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010

Conference

Conference2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010
Country/TerritoryMalaysia
CityKuala Lumpur
Period15/06/1017/06/10

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