Paper Info
Title
A rapid automatic brain tumor detection method for MRI images using modified minimum error thresholding technique
Abstract
AbstractThis proposed work is aimed to develop a rapid automatic method to detect the brain tumor from T2-weighted MRI brain images using the principle of modified minimum error thresholding MET method. Initially, modified MET method is applied to produce well segmented and sub-structural clarity for MRI brain images. Further, using FCM clustering the appearance of tumor area is refined. The obtained results are compared with corresponding ground truth images. The quantitative measures of results were compared with the results of those conventional methods using the metrics predictive accuracy PA, dice coefficient DC, and processing time. The PA and DC values of the proposed method attained maximum value and processing time is minimum while compared to conventional FCM and k-means clustering techniques. This proposed method is more efficient and faster than the existing segmentation methods in detecting the tumor region from T2-weighted MRI brain images. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 77-85, 2015
Year
DOI
Venue
2015
10.1002/ima.22123
Periodicals
Keywords
DocType
Volume
brain tumor, clustering, segmentation, thresholding, Fuzzy c-means
Journal
25
Issue
ISSN
Citations 
1
0899-9457
1
PageRank 
References 
Authors
0.40
4
2
Name
Order
Citations
PageRank
Kalaiselvi T191.88
Nagaraja P210.40