Automated model-based tissue classification of MR images of the brain

Describes a fully automated method for model-based tissue classification of magnetic resonance (MR) images of the brain. The method interleaves classification with estimation of the model parameters, improving the classification at each iteration. The algorithm is able to segment single- and multi-spectral MR images, corrects for MR signal inhomogeneities, and incorporates contextual information by means of Markov random Fields (MRF's). A digital brain atlas containing prior expectations about the spatial location of tissue classes is used to initialize the algorithm. This makes the method fully automated and therefore it provides objective and reproducible segmentations. The authors have validated the technique on simulated as well as on real MR images of the brain.

[1]  Alan C. Evans,et al.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.

[2]  W. Eric L. Grimson,et al.  Adaptive Segmentation of MRI Data , 1995, CVRMed.

[3]  D. Louis Collins,et al.  Design and construction of a realistic digital brain phantom , 1998, IEEE Transactions on Medical Imaging.

[4]  Guido Gerig,et al.  Compensation of Spatial Inhomogeneity in MRI Based on a Parametric Bias Estimate , 1996, VBC.

[5]  G. Bruce Pike,et al.  Understanding Intensity Non-uniformity in MRI , 1998, MICCAI.

[6]  Stan Z. Li,et al.  Markov Random Field Modeling in Computer Vision , 1995, Computer Science Workbench.

[7]  Charles R. Meyer,et al.  Retrospective Correction of MRI Amplitude Inhomogeneities , 1995, CVRMed.

[8]  L. R. Dice.  Measures of the Amount of Ecologic Association Between Species , 1945 .

[9]  J. Besag.  On the Statistical Analysis of Dirty Pictures , 1986 .

[10]  Koenraad Van Leemput,et al.  Automated Segmentation of MS Lesions from Multi-channel MR Images , 1999, MICCAI.

[11]  Xavier Descombes,et al.  Fine Structures Preserving Markov Model for Image Processing , 1995 .

[12]  Guy Marchal,et al.  Unsupervised Regularized Classification of Multi-Spectral MRI , 1996, VBC.

[13]  Ron Kikinis,et al.  Markov random field segmentation of brain MR images , 1997, IEEE Transactions on Medical Imaging.

[14]  R. Gupta,et al.  Polynomial modeling and reduction of RF body coil spatial inhomogeneity in MRI , 1993, IEEE Trans. Medical Imaging.

[15]  Jun Zhang.  The mean field theory in EM procedures for Markov random fields , 1992, IEEE Trans. Signal Process..

[16]  Alan C. Evans,et al.  An Extensible MRI Simulator for Post-Processing Evaluation , 1996, VBC.

[17]  J. W. Modestino,et al.  Use of the mean-field approximation in an EM-based approach to unsupervised stochastic model-based image segmentation , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[18]  Paul Suetens,et al.  Automated bias field correction and tissue classification of MR images of the brain using a digital atlas , 1999 .

[19]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[20]  H. Donald Gage,et al.  Statistical models of partial volume effect , 1995, IEEE Trans. Image Process..

[21]  Koenraad Van Leemput,et al.  Quantification of Cerebral Grey and White Matter Asymmetry from MRI , 1999, MICCAI.

[22]  E. Ising.  Beitrag zur Theorie des Ferromagnetismus , 1925 .

[23]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[24]  David H. Laidlaw,et al.  Partial-volume Bayesian classification of material mixtures in MR volume data using voxel histograms , 1997, IEEE Transactions on Medical Imaging.

[25]  D R Haynor,et al.  Partial volume tissue classification of multichannel magnetic resonance images-a mixel model. , 1991, IEEE transactions on medical imaging.

[26]  W. Eric L. Grimson,et al.  Enhanced Spatial Priors for Segmentation of Magnetic Resonance Imagery , 1998, MICCAI.

[27]  Guy Marchal,et al.  Multi-modality image registration by maximization of mutual information , 1996, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.

[28]  Koenraad Van Leemput,et al.  Automatic Segmentation of Brain Tissues and MR Bias Field Correction Using a Cigital Brain Atlas , 1998, MICCAI.

[29]  Benoit M. Dawant,et al.  Morphometric analysis of white matter lesions in MR images: method and validation , 1994, IEEE Trans. Medical Imaging.

[30]  New York Dover,et al.  ON THE CONVERGENCE PROPERTIES OF THE EM ALGORITHM , 1983 .

[31]  Nicholas Ayache,et al.  Bias Field Correction of Breast MR Images , 1996, VBC.

[32]  Koenraad Van Leemput,et al.  Automated model-based bias field correction of MR images of the brain , 1999, IEEE Transactions on Medical Imaging.

[33]  Alan C. Evans,et al.  BrainWeb: Online Interface to a 3D MRI Simulated Brain Database , 1997 .

[34]  Benoit M. Dawant,et al.  Correction of intensity variations in MR images for computer-aided tissue classification , 1993, IEEE Trans. Medical Imaging.

[35]  Jean-Philippe Thirion,et al.  Non-rigid matching using demons , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.