Level Set Based Segmentation with Intensity and Curvature Priors

  • Authors:
  • Michael E. Leventon;W. Eric L. Grimson;Olivier Faugeras;William M. Wells III

  • Affiliations:
  • -;-;-;-

  • Venue:
  • MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
  • Year:
  • 2000

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Abstract

A method is presented for segmentation of anatomical structures that incorporates prior information about the intensity and curvature profile of the structure from a training set of images and boundaries. Specifically, we model the intensity distribution as a function of signed distance from the object boundary, instead of modeling only the intensity of the object as a whole. A curvature profile acts as a boundary regularization term specific to the shape being extracted, as opposed to simply penalizing high curvature. Using the prior model, the segmentation process estimates a maximum a posteriori higher dimensional surface whose zero level set converges on the boundary of the object to be segmented. Segmentation results are demonstrated on synthetic data and magnetic resonance imagery.