Segmentation of the human trachea using deformable statistical models of tubular shapes

Authors:
Romulo Pinho;Jan Sijbers;Toon Huysmans
Affiliations:
University of Antwerp, Physics Department, VisionLab, Belgium;University of Antwerp, Physics Department, VisionLab, Belgium;University of Antwerp, Physics Department, VisionLab, Belgium
Venue:
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Year:
2007

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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.