IMPROVEMENT IN DETECTION ACCURACY OF DIGITAL MAMMOGRAM USING POINT TRANSFORM AND DATA MINING TECHNIQUE
Abstract
vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff241a2800000098fa010001000200
Cancer is one of the dangerous diseases faced by humans. Every one out of 100 women is facing breast cancer. So, to overcome this huge ratio many researches are being carried out. Prevention is better than cure; this paper presents one such attempt of detecting breast cancer in the early stages. In proposed method exponential point transform is carried out for image enhancement and in preprocessing stage pectoral mass is removed from the mammogram image. As the next step we apply K-means algorithm and morphological processing to identify the infected region and removal of unwanted region. Finally, Decision Tree Data mining technique is used for classifying features to detect presence of tumor. Hence by this approach we get more accurate results. The experimental results gave an accuracy of 97.03 %.

Authors
S P Meharunnisa, M Ravishanakr, K Suresh
Visvesvaraya Technological University, India

Keywords
Breast Cancer, Point Transform, K-means, Decision Tree Classifier
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
010000000000
Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 9 , Issue: 1 , Pages: 1838-1843 )
Date of Publication :
August 2018
Page Views :
123
Full Text Views :
2

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.