Paper Info
Title
A Hybrid Scheme for Breast Cancer Detection using Intuitionistic Fuzzy Rough Set Technique
Abstract
AbstractDiagnosis of cancer is of prime concern in recent years. Medical imaging is used to analyze these diseases. But, these images contain uncertainties due to various factors and thus intelligent techniques are essential to process these uncertainties. This paper hybridizes intuitionistic fuzzy set and rough set in combination with statistical feature extraction techniques. The hybrid scheme starts with image segmentation using intuitionistic fuzzy set to extract the zone of interest and then to enhance the edges surrounding it. Further feature extraction using gray-level co-occurrence matrix is presented. Additionally, rough set is used to engender all minimal reducts and rules. These rules then fed into a classifier to identify different zones of interest and to check whether these points contain decision class value as either cancer or not. The experimental analysis shows the overall accuracy of 98.3% and it is higher than the accuracy achieved by hybridizing fuzzy rough set model.
Year
DOI
Venue
2016
10.4018/IJHISI.2016040103
Periodicals
Keywords
Field
DocType
Automorphism, Hesitation, Indiscernibility Relation, Intuitionistic Fuzzy Set, Object Region, Restricted Equivalence Function, Rough Set
Data mining,Fuzzy classification,Fuzzy set operations,Fuzzy set,Feature extraction,Image segmentation,Rough set,Fuzzy number,Medicine,Dominance-based rough set approach
Journal
Volume
Issue
ISSN
11
2
1555-3396
Citations 
PageRank 
References 
2
0.38
0
Authors
2
Name
Order
Citations
PageRank
Chiranji Lal Chowdhary1282.62
D. P. Acharjya2608.98