Spatial Models for Fuzzy Clustering

D. L. Pham, J. L. Prince, A. P. Dagher, and, C. Xu, An automated technique for statistical characterization of brain tissues in magnetic resonance imaging, Int. J. Pattern Recognit. Artificial Intell, to appear (Tech. Rep. JHU/ECE 96–13).

Bezdek, 1993, Review of MR image segmentation techniques using pattern recognition, Med. Phys., 20, 1033, 10.1118/1.597000

Rignot, 1992, Unsupervised segmentation of polarimetric SAR data using the covariance matrix, IEEE Trans. Geosci. Remote Sensing, 30, 697, 10.1109/36.158863

Chumsamrong, 2000, Syntetic aperture radar (SAR) image segmentation using a new modified fuzzy c-means algorithm, Proceedings of Geoscience and Remote Sensing Symposium, 2, 624

Tolias, 1998, On applying spatial constraints in fuzzy image clustering using a fuzzy rule-based system, IEEE Signal Process. Lett., 5, 245, 10.1109/97.720555

Pardo, 2000, Vector probability diffusion, Proceedings of the 2000 Int'l Conf. on Image Processing, 1, 884

Tolias, 1998, Image segmentation by a fuzzy clustering algorithm using adaptive spatially constrained membership functions, IEEE Trans. Systems, Man, Cybernet. A, 28, 359, 10.1109/3468.668967

Acton, 2000, Scale space classification using area morphology, IEEE Trans. Image Process., 9, 623, 10.1109/83.841939

Liew, 2000, Fuzzy image clustering incorporating spatial continuity, IEE Proc. Visual Image Signal Process., 147, 185, 10.1049/ip-vis:20000218

Geman, 1984, Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images, IEEE Trans. Pattern Anal. Machine Intell., 6, 721, 10.1109/TPAMI.1984.4767596

Castagno, 1998, Video segmentation based on multiple features for interactive multimedia applications, IEEE Trans. Circuits Systems Video Technol., 8, 562, 10.1109/76.718503

Krishnapuram, 1993, A possibilistic approach to clustering, IEEE Trans. Fuzzy Systems, 1, 98, 10.1109/91.227387

Pham, 1999, Adaptive fuzzy segmentation of magnetic resonance images, IEEE Trans. Med. Imaging, 18, 737, 10.1109/42.802752

Gath, 1987, Unsupervised optimal fuzzy clustering, IEEE Trans. Pattern Anal. Machine Intell., 11, 773, 10.1109/34.192473

Xie, 1991, A validity measure for fuzzy clustering, IEEE Trans. Pattern Anal. Machine Intell., 13, 841, 10.1109/34.85677

Zhang, 1992, The mean field theory in EM procedures for Markov random fields, IEEE Trans. Signal Process., 40, 2570, 10.1109/78.157297

Bezdek, 1980, A convergence theorem for the fuzzy ISODATA clustering algorithms, IEEE Trans. Pattern Anal. Machine Intell., 2

Pham, 1999, An adaptive fuzzy c-means algorithm for image segmentation in the presence of intensity inhomogeneities, Pattern Recognit. Lett., 20, 57, 10.1016/S0167-8655(98)00121-4

Wahba, 1990, Spline Models for Observational Data, 59

Reeves, 1992, A cross-validation framework for solving image restoration problems, J. Visual Comm. Image Represent., 3, 433, 10.1016/1047-3203(92)90044-T

Collins, 1998, Design and construction of a realistic digital brain phantom, IEEE Trans. Med. Imaging, 17, 463, 10.1109/42.712135

Brandt, 1994, Estimation of CSF, white and gray matter volumes in hydrocephalic children using fuzzy clustering of MR images, Comput. Med. Imaging Graphics, 18, 25, 10.1016/0895-6111(94)90058-2

Thompson, 1991, A study of methods of choosing the smoothing paramter in image restoration by regularization, IEEE Trans. Pattern Anal. Machine Intell., 13, 326, 10.1109/34.88568

Galatsanos, 1992, Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation, IEEE Trans. Image Process., 1, 322, 10.1109/83.148606