Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C -Means Clustering
Joint Authors
Wu, Jianhuang
Hu, Qingmao
Elazab, Ahmed
Wang, Changmiao
Jia, Fucang
Li, Guanglin
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-17
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
An adaptively regularized kernel-based fuzzy C -means clustering framework is proposed for segmentation of brain magnetic resonance images.
The framework can be in the form of three algorithms for the local average grayscale being replaced by the grayscale of the average filter, median filter, and devised weighted images, respectively.
The algorithms employ the heterogeneity of grayscales in the neighborhood and exploit this measure for local contextual information and replace the standard Euclidean distance with Gaussian radial basis kernel functions.
The main advantages are adaptiveness to local context, enhanced robustness to preserve image details, independence of clustering parameters, and decreased computational costs.
The algorithms have been validated against both synthetic and clinical magnetic resonance images with different types and levels of noises and compared with 6 recent soft clustering algorithms.
Experimental results show that the proposed algorithms are superior in preserving image details and segmentation accuracy while maintaining a low computational complexity.
American Psychological Association (APA)
Elazab, Ahmed& Wang, Changmiao& Jia, Fucang& Wu, Jianhuang& Li, Guanglin& Hu, Qingmao. 2015. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C -Means Clustering. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057915
Modern Language Association (MLA)
Elazab, Ahmed…[et al.]. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C -Means Clustering. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1057915
American Medical Association (AMA)
Elazab, Ahmed& Wang, Changmiao& Jia, Fucang& Wu, Jianhuang& Li, Guanglin& Hu, Qingmao. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C -Means Clustering. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1057915
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057915