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Surface Extraction from Volumetric Images Using Deformable Meshes: A Comparative Study

  • Jussi Tohka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2352)

Abstract

Deformable models are by their formulation able to solve surface extraction problem from noisy volumetric images. This is since they use image independent information, in form of internal energy or internal forces, in addition to image data to achieve the goal. However, it is not a simple task to deform initially given surface meshes to a good representation of the target surface in the presence of noise. Several methods to do this have been proposed and in this study a few recent ones are compared. Basically, we supply an image and an arbitrary but reasonable initialization and examine how well the target surface is captured with different methods for controlling the deformation of the mesh. Experiments with synthetic images as well as medical images are performed and results are reported and discussed. With synthetic images, the quality of results is measured also quantitatively. No optimal method was found, but the properties of different methods in distinct situations were highlighted.

Keywords

External Force Active Contour Synthetic Image Deformable Model Active Contour Model 
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 2002

Authors and Affiliations

  • Jussi Tohka
    • 1
  1. 1.DMI / Institute of Signal ProcessingTampere University of TechnologyFinland

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