A statistical process for surface tracking

  • Nigel G. Sharp
  • Edwin R. Hancock
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1176)


This paper describes a novel approach to surface tracking in volumetric image stacks. It draws on a statistical model of the uncertainties inherent in the characterisation of feature contours to compute an evidential field for putative inter-frame displacements. This field is computed using Gaussian density kernels which are parameterised in terms of the variance-covariance matrices for contour displacement. The underlying variance model accommodates the effects of raw image noise on the estimated surface normals. The evidential field effectively couples contour displacements to the intensity features on successive frames through a statistical process of contour tracking. Hard contours are extracted using a dictionary-based relaxation process. The method is evaluated on both MRI data and simulated data.


Volumetric Image Feature Contour Surface Tracking Contour Displacement Contour Tracking 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Nigel G. Sharp
    • 1
  • Edwin R. Hancock
    • 1
  1. 1.Department of Computer ScienceUniversity of YorkUK

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