(3.81.73.233)
Users online: 26883    [ij] [ij] [ij] 
Email id
 

Indian Journal of Public Health Research & Development
Year : 2019, Volume : 10, Issue : 5
First page : ( 786) Last page : ( 791)
Print ISSN : 0976-0245. Online ISSN : 0976-5506.
Article DOI : 10.5958/0976-5506.2019.01108.2

Computer Aided classification of breast Lesions in Digital Mammograms

Sangeethapriya K.1,*, Dhivya Josephin Arockia1, Thamizhvani T. R.1, Hemalatha R. J.1

1Department of Biomedical Engineering, Vels Institute of Science Technology and Advanced Studies, Chennai, India

*Corresponding Author: K. Sangeethapriya, Department of Biomedical Engineering, Vels Institute of Science Technology and Advanced Studies, Chennai, India, Email: sangeetha.se@velsuniv.ac.in

Online published on 4 June, 2019.

Abstract

Objective

Mammography technique is mostly used for detecting the presence of abnormal breast lesions among women. Differentiating these abnormalities is a most difficult task faced by the radiologists. By using this proposed technique the rate of unnecessary biopsies can be limited. This paper deals with an effective way of detecting the breast lesions using curvelet transform. This proposed paper follows a stepwise procedure such as (a) Preprocessing(b) Region of Interest Segmentation. (c) Applying Curvelet Transform (d)Feature Extraction & finally (e)Classification of features using different kernels of SVM. It is inferred from the observed results that the SVM(Linear) classifier showed a good accuracy rate of 80%.

Top

Keywords

Mammogram, MIAS Database, Cancer Detection, Benign, Malignant, Curvelet transform.

Top

  
║ Site map ║ Privacy Policy ║ Copyright ║ Terms & Conditions ║ Page Rank Tool
375,243,752 visitor(s) since 30th May, 2005.
All rights reserved. Site designed and maintained by DIVA ENTERPRISES PVT. LTD..
Note: Please use Internet Explorer (6.0 or above). Some functionalities may not work in other browsers.