MRFSEG+GAMIXTURE is a collection of tools implementing a flexible voxel classification framework. The framework is based on a novel genetic algorithm based finite mixture model (GAMIXTURE) and a standard 3-D Markov random field (MRF) based on the iterative conditional modes (ICM) algorithm (MRFSEG).


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  • MRFSEG is programmed to automatically classify voxel into tissue types in 3-D images while modeling the spatial interactions of the voxel labels by an MRF.
  • GAMIXTURE is a program that implements a new genetic algorithm based finite mixture model (FMM) parameter estimation scheme. This allows for robustly finding parameters for an almost arbitrary 1-d FMM. However, at the moment Gaussian densities are used to model the pure tissue types.


MRFSEG+GAMIXTURE Software Bundle Support


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Version: 1.1 (beta)
Release Date:  2007-08-07
Developer(s): Jussi Tohka
License: LONI Software License
File Size: 141 Kb
SYSTEM REQUIREMENTS OS: tested using Linux kernels 2.4 and 2.6., Memory: The memory requirements depend on the size of the image to be tissue classified and the number of ti, Processor: N/a
J. Tohka, I.D. Dinov, D.W. Shattuck, and A.W. Toga. GAMIXTURE+MRFSEG: "A flexible tool for voxel classification" In proc. of Nordic Neuroinformatics Workshop, pp. 10, 2007.
J. Tohka, I.D. Dinov, D.W. Shattuck, and A.W. Toga. "Brain MRI Segmentation Based on Local Markov Random Fields and Sub Volume Probabilistic Atlases" 14th Annual Meeting of the Organization of Human Brain Mapping, Melbourne, Australia, 2008.
J. Tohka, E. Krestyannikov, I.D. Dinov, A. MacKenzie-Graham, D.W. Shattuck, U. Ruotsalainen, and A.W. Toga. "Genetic algorithms for finite mixture model based voxel classification in neuroimaging" IEEE Transactions on Medical Imaging, 26(5):696 - 711, 200
This work was supported by:
NIH-NCRR 9P41EB015922-15 and 2-P41-RR-013642-15
NIH-NCRR U54 RR021813
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