A new medical decision system to identify breast cancer

Author

Gargouri Ben Ayed, Norhene ; Larousi, Malek Gargouri ; Masmoudi, Alima Dammak ; Masmoudi, Dorra Sellami ; Abid, Riadh

Author_Institution

CEM Lab., Univ. of Sfax, Sfax, Tunisia

fYear

2014

fDate

17-19 Jan. 2014

Firstpage

1

Lastpage

5

Abstract

An improved computer system has been presented to classify the mass and identify the different stages of breast cancer using artificial neural network (ANN). In this paper, we extract texture and shape features. The accuracy of the proposed system is 99.5%. The images from Farabi digital database for screening mammography have been applied for the development of the proposed system. This later may provide precious information to radiologists.

Keywords

cancer; feature extraction; image classification; image denoising; image enhancement; image texture; mammography; medical image processing; neural nets; ANN; Farabi digital database; artificial neural network; breast cancer identification; computer system; mass classification; medical decision system; screening mammography; shape feature extraction; texture feature extraction; Artificial neural networks; Cancer; Electric shock; Feature extraction; Image segmentation; Shape; Tumors; Artificial neural network; Breast cancer; feature extraction; image denoising and enhancement; mammogram; satges;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Applications and Information Systems (WCCAIS), 2014 World Congress on

Conference_Location

Hammamet

Print_ISBN

978-1-4799-3350-1

Type

conf

DOI

10.1109/WCCAIS.2014.6916603

Filename

6916603