Paper Info
Title
Dynamic Incorporation Of Wavelet Filter In Fuzzy C-Means For Efficient And Noise-Insensitive Mr Image Segmentation
Abstract
Image intensity in magnetic resonance (MR) images in the presence of noise obeys Rician distribution. The signal-dependent Rician noise makes accurate image segmentation a challenging task. Although existing fuzzy c-means (FCM) variants with local filters improve the segmentation performance, they are less effective for reducing the negative effect from Rician noise, and the repeatedly applied filter increases their computational intensiveness. To address this issue, we propose a novel image segmentation method which dynamically incorporates wavelet-based noise detector and filter in the FCM membership function. The modified algorithm is designed to exploit both frequency and spatial information in the images and minimizes clustering errors caused by Rician noise. Furthermore, efficiency of the proposed method can be enhanced by the strategy of applying filter only when noise is detected. The experimental results of segmentation on synthetic and brain MR images, demonstrate the computational efficiency and noiseinsensitivity of the proposed method.
Year
DOI
Venue
2015
10.1080/18756891.2015.1063241
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
Keywords
Field
DocType
MR images, segmentation, fuzzy c-means, clustering, wavelet, Rician noise
Scale-space segmentation,Computer science,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Cluster analysis,Wavelet,Computer vision,Pattern recognition,Segmentation,Membership function,Machine learning,Rician fading
Journal
Volume
Issue
ISSN
8
5
1875-6891
Citations 
PageRank 
References 
3
0.38
12
Authors
6
Name
Order
Citations
PageRank
Shang-Ling Jui1123.95
Chao Lin250.78
Weichen Xu330.38
Weiyao Lin473268.05
Dongmei Wang582.17
Kai Xiao6152.96