Flash News
Welcome to IARC

Publisher Login

Latest News
Welcome to IARC- JCR Report

Submit your Journal to get IARC-JCRR Indexing and Impact Factor
 

Impact Factor calculated by IARC on the basis of Journal Citation Reference (JCR) Report.

 

Contact: iarcdpi@gmail.com

 

CUCKOO SEARCH: AN OPTIMIZED WAY FOR MAMMOGRAM FEATURE SELECTION
Deepika K. Nagthane, Dr. A.M.Rajurkar

Published in: International Journal of Current Engineering And Scientific Research ( IJCESR)
Volume- 4, Issue-8, pp.81-86, Aug 2017
DPI :-> 16.10046.IJCESR.2017.V4I8.8186.1908



Abstract
One of the main reasons for increase in mortality rate of woman is breast cancer. Accurate early detection of breast cancer seems to be the only solution for the diagnosis. In the field of breast cancer research, many new computer aided diagnosis systems have been developed to reduce the diagnostic test false positives because of the subtle appearance of the breast cancer tissues. This paper investigates a new approach for the breast cancer classification system using mammogram images. The proposed method uses Cuckoo Search based feature selection algorithm to select optimal feature split points. Classification is based on decision tree classifier based on association rule agreements. The experimentation of proposed method on MIAS database resulted in classification of normal and abnormal cancerous mammogram The result proves the efficacy of the proposed method in classifying task.

Key-Words / Index Term
Breast cancer, digital mammography, Cuckoo search, Decision tree classifier, Association rule

How to cite this article
Deepika K. Nagthane, Dr. A.M.Rajurkar , “ CUCKOO SEARCH: AN OPTIMIZED WAY FOR MAMMOGRAM FEATURE SELECTION”, International Journal of Current Engineering And Scientific Research ( IJCESR), 4, Issue-8, pp.81-86, Aug 2017. DPI:16.10046.IJCESR.V4.I8.1908