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Segmentation of the Human Trachea Using Deformable Statistical Models of Tubular Shapes

  • Romulo Pinho
  • Jan Sijbers
  • Toon Huysmans
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4678)

Abstract

In this work, we present two active shape models for the segmentation of tubular objects. The first model is built using cylindrical parameterization and minimum description length to achieve correct correspondences. The other model is a multidimensional point distribution model built from the centre line and related information of the training shapes. The models are used to segment the human trachea in low-dose CT scans of the thorax and are compared in terms of compactness of representation and segmentation effectiveness and efficiency. Leave-one-out tests were carried out on real CT data.

Keywords

Abdominal Aortic Aneurysm Abdominal Aortic Aneurysm Iterative Close Point Minimum Description Length Tracheal Stenosis 
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 2007

Authors and Affiliations

  • Romulo Pinho
    • 1
  • Jan Sijbers
    • 1
  • Toon Huysmans
    • 1
  1. 1.University of Antwerp, Physics Department, VisionLabBelgium

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