Fuzzy C-mean based brain MRI segmentation algorithms

Authors:
M. A. Balafar
Affiliations:
Department of Computer, Faculty of Engineering, University of Tabriz, Tabriz, East Azerbaijan, Iran
Venue:
Artificial Intelligence Review
Year:
2014

Citing 15
Cited 0

Characterization and detection of noise in clustering

Pattern Recognition Letters
An adaptive fuzzy C-means algorithm for image segmentation in the presence of intensity inhomogeneities

Pattern Recognition Letters
Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms
Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation

Pattern Recognition
An new initialization method for fuzzy c-means algorithm

Fuzzy Optimization and Decision Making
Review of brain MRI image segmentation methods

Artificial Intelligence Review
A new method for MR grayscale inhomogeneity correction

Artificial Intelligence Review
MRI fuzzy segmentation of brain tissue using neighborhood attraction with neural-network optimization

IEEE Transactions on Information Technology in Biomedicine
Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image segmentation by a fuzzy clustering algorithm using adaptive spatially constrained membership functions

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A novel kernelized fuzzy C-means algorithm with application in medical image segmentation

Artificial Intelligence in Medicine
A possibilistic approach to clustering

IEEE Transactions on Fuzzy Systems
Scale space classification using area morphology

IEEE Transactions on Image Processing
A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain

IEEE Transactions on Neural Networks
New spatial based MRI image de-noising algorithm

Artificial Intelligence Review

Quantified Score

Hi-index	0.00

Visualization

Abstract

Brain image segmentation is one of the most important parts of clinical diagnostic tools. Fuzzy C-mean (FCM) is one of the most popular clustering based segmentation methods. In this paper, a review of the FCM based segmentation algorithms for brain MRI images is presented. The review covers algorithms for FCM based segmentation algorithms, their comparative evaluations based on reported results and the result of experiments for neighborhood based extensions for FCM.