MRI mammogram image classification using ID3 algorithm

Author

Angayarkanni, A.S.P. ; Kamal, B.D.N.B.

Author_Institution

Dept. of Comput. Sci., Lady Doak Coll., Madurai, India

fYear

2012

fDate

3-4 July 2012

Firstpage

1

Lastpage

5

Abstract

Breast cancer is one of the most common forms of cancer in women. In order to reduce the death rate , early detection of cancerous regions in mammogram images is needed. The existing system is not so accurate and it is time consuming. The Proposed system is mainly used for automatic segmentation of the mammogram images and classify them as benign,malignant or normal based on the decision tree ID3 algorithm. A hybrid method of data mining technique is used to predict the texture features which play a vital role in classification. The sensitivity, the specificity, positive prediction value and negative prediction value of the proposed algorithm accounts to 93.45% , 99.95%,94% and 98.5% which rates very high when compared to the existing algorithms. The size and the stages of the tumor is detected using the ellipsoid volume formula which is calculated over the segmented region.

Keywords

biomedical MRI; cancer; data mining; decision trees; image classification; image segmentation; image texture; mammography; medical image processing; prediction theory; tumours; MRI mammogram image classification; breast cancer; cancerous region detection; data mining; death rate reduction; decision tree ID3 algorithm; ellipsoid volume formula; mammogram image segmentation; negative prediction value; positive prediction value; texture feature prediction; tumor size detection; tumor stage detection; women; GLCM; SOM and ID3 algorithm; Texture;

fLanguage

English

Publisher

iet

Conference_Titel

Image Processing (IPR 2012), IET Conference on

Conference_Location

London

Electronic_ISBN

978-1-84919-632-1

Type

conf

DOI

10.1049/cp.2012.0464

Filename

6290659