Abstract
Evolutionary algorithms with global search capabilities have been successfully used to replace local search heuristics in statistical image segmentation. Among them, a novel immune-inspired evolutionary method, clonal selection algorithm (CSA) has proven itself in a variety of real applications with better performance than several other evolutionary algorithms. In this paper, we incorporate the CSA into the Gaussian mixture model (GMM) based image segmentation process, and thus propose the CSA-GMM algorithm for delineating gray matter, white matter and cerebrospinal fluid in brain MR images. In this algorithm, we assume that brain voxel values to be modeled by the GMM, whose parameters are then estimated by using the CSA. Each brain voxel is then categorized by applying the voxel value and statistical parameters to the Bayes classifier. In order to improve segmentation performance by employing the spatial information, we also construct the probabilistic brain atlas for each image, and incorporate the anatomical priors embedded in the atlas into the segmentation process. The proposed algorithm has been evaluated in simulated brain MR images and been compared to the GA-EM algorithm and the segmentation routines used in the statistical parametric mapping (SPM) package and FMRIB Software library (FSL) in 18 clinical T1-weighted brain MR images. Our results show that the proposed CSA-GMM algorithm can achieve better segmentation accuracy on average.
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References
Zhang, Y., Brady, M., Smith, S.: Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Transactions on Medical Imaging 20, 45–57 (2001)
Van Leemput, K., Maes, F., Vandermeulen, D., Suetens, P.: Automated model-based tissue classification of MR images of the brain. IEEE Transactions on Medical Imaging 18, 897–908 (1999)
Heckemann, R.A., Hajnal, J.V., Aljabar, P., Rueckert, D., Hammers, A.: Automatic anatomical brain MRI segmentation combining label propagation and decision fusion. NeuroImage 33, 115–126 (2006)
Tohka, J., Krestyannikov, E., Dinov, I.D., Graham, A.M., Shattuck, D.W., Ruotsalainen, U., Toga, A.W.: Genetic Algorithms for Finite Mixture Model Based Voxel Classification in Neuroimaging. IEEE Transactions on Medical Imaging 26, 696–711 (2007)
Tian, G., Xia, Y., Zhang, Y., Feng, D.: Hybrid Genetic and Variational Expectation-Maximization Algorithm for Gaussian-Mixture-Model-Based Brain MR Image Segmentation. IEEE Transactions on Information Technology in Biomedicine 15, 373–380 (2011)
Fischl, B., Salat, D.H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., Montillo, A., Makris, N., Rosen, B., Dale, A.M.: Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain. Neuron. 33, 341–355 (2002)
Castro, L.N.D., Zuben, F.J.V.: Clonal Selection Algorithm with Engineering Applications. In: Workshop on Artificial Immune Systems and Their Applications, GECCO 2000, Las Vegas, USA, pp. 36–37 (2000)
de Castro, L.N., Zuben, F.J.V.: Learning and optimization using the clonal selection principle. IEEE Transactions on Evolutionary Computation 6 (2002)
BrainWeb: Simulated Brain Database, http://mouldy.bic.mni.mcgill.ca/brainweb/
Statistical Parameter Mapping, http://www.fil.ion.ucl.ac.uk/spm/software/spm8/
FMRIB Software Library, http://fsl.fmrib.ox.ac.uk/fsl/
The Internet Brain Segmentation Repository, http://www.cma.mgh.harvard.edu/ibsr
Bharatha, A., Hirose, M., Hata, N., Tempany, C.M., et al.: Evaluation of three-dimensional finite element-based deformable registration of pre- and intra-operative prostate imaging. Medical Physics 28 (2001)
MIXTUREGA, http://www.cs.tut.fi/~jupeto/gamixture.html
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Zhang, T., Xia, Y., Feng, D.D. (2012). Clonal Selection Algorithm for Gaussian Mixture Model Based Segmentation of 3D Brain MR Images. In: Zhang, Y., Zhou, ZH., Zhang, C., Li, Y. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2011. Lecture Notes in Computer Science, vol 7202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31919-8_38
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DOI: https://doi.org/10.1007/978-3-642-31919-8_38
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