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

Author

Eltoukhy, Mohamed Meselhy ; Faye, Ibrahima ; Samir, Brahim Belhaouari

Author_Institution

Electr. & Electron. Eng. Dept., Univ. Teknol. PETRONAS, Bandar Seri Iskandar, Malaysia

fYear

2010

fDate

15-17 June 2010

Firstpage

1

Lastpage

5

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.

Keywords

biological organs; cancer; curvelet transforms; feature extraction; image classification; image texture; mammography; medical image processing; tumours; Euclidian distance; benign tumor; breast cancer diagnosis; curvelet transform; digital mammogram; feature extraction; malignant tumor; nearest neighbor classifier; texture analysis; tissue tissues; Breast cancer; Classification algorithms; Feature extraction; Image resolution; Support vector machine classification; Transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent and Advanced Systems (ICIAS), 2010 International Conference on

Conference_Location

Kuala Lumpur, Malaysia

Print_ISBN

978-1-4244-6623-8

Type

conf

DOI

10.1109/ICIAS.2010.5716125

Filename

5716125