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A Tracking Approach to Parcellation of the Cerebral Cortex

  • Chris Adamson
  • Leigh Johnston
  • Terrie Inder
  • Sandra Rees
  • Iven Mareels
  • Gary Egan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3749)

Abstract

The cerebral cortex is composed of regions with distinct laminar structure. Functional neuroimaging results are often reported with respect to these regions, usually by means of a brain “atlas”. Motivated by the need for more precise atlases, and the lack of model-based approaches in prior work in the field, this paper introduces a novel approach to parcellating the cortex into regions of distinct laminar structure, based on the theory of target tracking. The cortical layers are modelled by hidden Markov models and are tracked to determine the Bayesian evidence of layer hypotheses. This model-based parcellation method, evaluated here on a set of histological images of the cortex, is extensible to 3-D images.

Keywords

Cerebral Cortex Hide Markov Model Target Tracking Transition Probability Matrix Laminar Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Garey, L.J.: Brodmann’s Localisation in the Cerebral Cortex. Smith-Gordon, London (1994)Google Scholar
  2. 2.
    Schleicher, A., Amunts, K., Geyer, S., Morosan, P., Zilles, K.: Observer-Independent Method for Microstructural Parcellation of Cerebral Cortex: A Quantitative Approach to Cytoarchitectonics. NeuroImage 9, 165–177 (1999)CrossRefGoogle Scholar
  3. 3.
    Annese, J., Pitiot, A., Dinov, I.D., Toga, A.W.: A myelo-architectonic method for the structural classification of cortical areas. NeuroImage 21, 15–26 (2004)CrossRefGoogle Scholar
  4. 4.
    Adamson, C., Davies, R., Inder, T., Rees, S., Mareels, I., Egan, G.: Markov random field-based parcellation of the cerebral cortex: Application to histology images. In: ISSNIP 2004, vol. 1, pp. 559–564 (2004)Google Scholar
  5. 5.
    Kruggel, F., Brückner, M.K., Arendt, T., Wiggins, C.J., von Cramon, D.Y.: Analyzing the Neocortical Fine-Structure. Medical Image Analysis 7, 251–264 (2003)CrossRefGoogle Scholar
  6. 6.
    Xie, X., Evans, R.J.: Multiple target tracking and multiple frequency line tracking using hidden Markov models. IEEE Transactions on Signal Processing 39, 2659–2676 (1991)zbMATHCrossRefGoogle Scholar
  7. 7.
    Walters, N., Egan, G., Kril, J., Kean, M., Waley, P., Jenkinson, M., Watson, J.: In vivo Identification of Human Cortical Areas using High-Resolution MRI: An Approach to Cerebral Structure-Function Correlation. Proceedings of the National Academy of Sciences 100, 2981–2986 (2003)CrossRefGoogle Scholar
  8. 8.
    Barbier, E.L., Marrett, S., Danek, A., Vortmeyer, A., van Gelderen, P., Duyn, J., Bandettini, P., Grafman, J., Koretsky, A.P.: Imaging Cortical Anatomy by High-Resolution MR at 3.0T: Detection of the Stripe of Gennari in Visual Area 17. Magnetic Resonance in Medicine 48, 735–738 (2002)CrossRefGoogle Scholar
  9. 9.
    Bridge, H., Clare, S., Jenkinson, M., Jezzard, P., Parker, A.J., Matthews, P.M.: Independent anatomical and functional measures of the V1/V2 boundary in human visual cortex. Journal of Vision 5, 93–102 (2005)CrossRefGoogle Scholar
  10. 10.
    Jones, S.E., Buchbinder, B.R., Aharon, I.: Three-Dimensional Mapping of Cortical Thickness Using Laplace’s Equation. Human Brain Mapping 11, 12–32 (2002)CrossRefGoogle Scholar
  11. 11.
    Rabiner, L.R.: A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 77, 257–286 (1989)CrossRefGoogle Scholar
  12. 12.
    Elder, J.H., Krupnik, A., Johnston, L.A.: Contour Grouping with Prior Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 661–674 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Chris Adamson
    • 1
    • 2
  • Leigh Johnston
    • 1
  • Terrie Inder
    • 1
  • Sandra Rees
    • 4
  • Iven Mareels
    • 2
  • Gary Egan
    • 1
    • 3
  1. 1.Howard Florey InstituteUniversity of MelbourneAustralia
  2. 2.Dept. of Electrical and Electronic EngineeringUniv. of MelbourneAustralia
  3. 3.Centre For NeuroscienceUniversity of MelbourneAustralia
  4. 4.Department of Anatomy and Cell BiologyUniversity of MelbourneAustralia

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