Markov random field modeling in computer vision
Markov random field modeling in computer vision
Automatical Adaption of the Stereotactical Coordinate System in Brain MRI Datasets
IPMI '97 Proceedings of the 15th International Conference on Information Processing in Medical Imaging
WBIA '98 Proceedings of the IEEE Workshop on Biomedical Image Analysis
A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Neural Networks
A parametric gradient descent MRI intensity inhomogeneity correction algorithm
Pattern Recognition Letters
A hierarchical genetic algorithm for segmentation of multi-spectral human-brain MRI
Expert Systems with Applications: An International Journal
Multi-stage FCM-Based Intensity Inhomogeneity Correction for MR Brain Image Segmentation
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Efficient feature extraction for fast segmentation of MR brain images
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Modified fuzzy c-means algorithm for segmentation of T1-T2-weighted brain MRI
Journal of Computational and Applied Mathematics
Modified bias field fuzzy C-means for effective segmentation of brain MRI
Transactions on computational science VIII
Modified bias field fuzzy C-means for effective segmentation of brain MRI
Transactions on computational science VIII
An efficient approach to intensity inhomogeneity compensation using c-means clustering models
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Efficient inhomogeneity compensation using fuzzy c-means clustering models
Computer Methods and Programs in Biomedicine
Hybrid softcomputing model for lesion identification and information combination: some case studies
International Journal of Data Mining and Bioinformatics
A modified fuzzy C-means algorithm for MR brain image segmentation
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Pattern Recognition Letters
Entropy maximization based segmentation, transmission and Wavelet Fusion of MRI images
International Journal of Hybrid Intelligent Systems
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The segmentation of magnetic resonance images (MRI) is a challenging problem that has received an enormous amount of attention lately. Many researchers have applied various techniques however fuzzy c-means (FCM) based algorithms have produced better results compared to other methods. In this paper, we present a modified FCM algorithm for bias (also called intensity in-homogeneities) estimation and segmentation of MRI. Normally, the intensity in-homogeneities are attributed to imperfections in the radio-frequency coils or to the problems associated with the image acquisition. Our algorithm is formulated by modifying the objective function of the standard FCM and it has the advantage that it can be applied at an early stage in an automated data analysis before a tissue model is available. The proposed method can deal with the intensity in-homogeneities and Gaussian noise effectively. We have conducted extensive experimental and have compared our results with other reported methods. The results using simulated images and real MRI data show that our method provides better results compared to standard FCM-based algorithms and other modified FCM-based techniques.