Statistical features and classification of normal and abnormal mammograms

Author

Ben Youssef, Youssef ; Abdelmounim, El Hassane ; Rabeh, Abderahmane ; Zbitou, J. ; Belaguid, Abdelaziz

Author_Institution

LASTI, Univ. Hassan 1st, Settat, Morocco

fYear

2014

fDate

14-16 April 2014

Firstpage

448

Lastpage

452

Abstract

Breast cancer affects many women. Early detection and timely medical intervention is the key to long term survival and life quality for patients. The algorithm proposed in this paper contains four steps: Image DATA, preprocessing, features extraction and classification. Images samples are acquired with X-ray or new technique Terahertz imaging, noise removal is performed in preprocessing, statistical method is used for feature extraction process and classification.

Keywords

cancer; feature extraction; image denoising; mammography; medical image processing; statistical analysis; terahertz wave imaging; X-ray technique; breast cancer; features classification; features extraction; image DATA; images samples; medical intervention; noise removal; preprocessing; statistical method; terahertz imaging; Biomedical imaging; Image segmentation; Irrigation; Robustness; Tumors; X-ray imaging; Computer Aided Detection (CAD); Terahertz (THz) imaging; feature extraction; mammography;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Computing and Systems (ICMCS), 2014 International Conference on

Conference_Location

Marrakech

Print_ISBN

978-1-4799-3823-0

Type

conf

DOI

10.1109/ICMCS.2014.6911225

Filename

6911225