An MCMC Feature Selection Technique for Characterizing and Classifying Spatial Region Data

  • Despina Kontos
  • Vasileios Megalooikonomou
  • Marc J. Sobel
  • Qiang Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3138)


We focus on characterizing spatial region data when distinct classes of structural patterns are present. We propose a novel statistical approach based on a supervised framework for reducing the dimensionality of the initial feature space, selecting the most discriminative features. The method employs the statistical techniques of Bootstrapping simulation, Bayesian Inference and Markov Chain Monte Carlo (MCMC), to indicate the most informative features, according to their discriminative power across the distinct classes of data. The technique assigns to each feature a weight proportional to its significance. We evaluate the proposed technique with classification experiments, using both synthetic and real datasets of 2D and 3D spatial ROIs and established classifiers (Neural Networks). Finally, we compare our method with other dimensionality reduction techniques.


  1. 1.
    Megalooikonomou, V., Ford, J., Shen, L., Makedon, F., Saykin, A.: Data mining in brain imaging. Statistical Methods in Medical Research 9(4), 359–394 (2000)zbMATHCrossRefGoogle Scholar
  2. 2.
    Guting, R.H.: An Introduction to Spatial Database Systems. VLDB Journal 3(4), 357–399 (1994)CrossRefGoogle Scholar
  3. 3.
    Loncaric, S.: A Survey of Shape Analysis Techniques. Pattern Recognition 31(8), 983–1001 (1998)CrossRefGoogle Scholar
  4. 4.
    Megalooikonomou, V., Dutta, H., Kontos, D.: Fast and Effective Characterization of 3D Region Data. In: Proc. of the IEEE International Conference on Image Processing (ICIP), Rochester, NY, pp. 421–424 (2002)Google Scholar
  5. 5.
    Carrerira-Peripinan, M.A.: A review of Dimension Reduction Techniques, Technical Report CS-96-09, Dept. of Computer Science, University of Sheffield (1997)Google Scholar
  6. 6.
    Petrakis, E.G.M., Faloutsos, C.: Similarity Searching in Medical Image DataBases. IEEE Trans. on Knowledge and Data Engineering 9(3), 435–447 (1997)CrossRefGoogle Scholar
  7. 7.
    Kruskal, J.B., Wish, M.: Multidimensional scaling. SAGE publications, Beverly Hills (1978)Google Scholar
  8. 8.
    Faloutsos, C., Ranganathan, M., Manolopoulos, Y.: Fast subsequence matching in timeseries databases. In: Proc. of the ACM SIGMOD Int.Conf. on Management of Data, Minneapolis, MN, pp. 419–429 (1994)Google Scholar
  9. 9.
    Chan, K.P., Fu. A.C.: Efficient time series matching by wavelets. In: Proc. of the Intl. Conference on Data Engineering ICDE, Sydney, Australia, pp. 126–133 (1999)Google Scholar
  10. 10.
    Fukunaga, K.: Introduction to Statistical Pattern Recognition, 2nd edn. Academic Press, New York (1990)zbMATHGoogle Scholar
  11. 11.
    Kohavi, R., John, G.: Wrappers for Feature Subset Selection. Artificial Intelligence 97(1-2), 273–324 (1997)zbMATHCrossRefGoogle Scholar
  12. 12.
    Jain, A., Duin, P., Mao, J.: Statistical pattern recognition: A review. IEEE Transactions on PAMI 22(1), 4–37 (2000)Google Scholar
  13. 13.
    Duin, R.P.W.: A Matlab Toolbox for Pattern Recognition, PRTools Version 3.0 (2000)Google Scholar
  14. 14.
    Saykin, A.J., Flashman, L.A., Frutiger, S.A., Johnson, S.C., Mamourian, A.C., Moritz, C.H., O’Jile, J.R., Riordan, H.J., Santulli, R.B., Smith, C.A., Weaver, J.B.: Neuroanatomic substrates of semantic memory impairment in Alzheimer’s disease: Patterns of functional MRI activation. Journal of the International Neuropsychological Society 5, 377–392 (1999)CrossRefGoogle Scholar
  15. 15.
    Megalooikonomou, V., Kontos, D., Pokrajac, D., Lazarevic, A., Obradovic, Z., Boyko, O., Saykin, A., Ford, J., Makedon, F.: Classification and Mining of Brain Image Data Using Adaptive Recursive Partitioning Methods: Application to Alzheimer Disease and Brain Activation Patterns. In: Human Brain Mapping Conference (OHBM 2003), New York, NY (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Despina Kontos
    • 1
  • Vasileios Megalooikonomou
    • 1
  • Marc J. Sobel
    • 2
  • Qiang Wang
    • 1
  1. 1.Department of Computer and Information SciencesTemple UniversityPhiladelphiaUSA
  2. 2.Department of StatisticsTemple UniversityPhiladelphiaUSA

Personalised recommendations