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Topo-Geometric Filtration Scheme for Geometric Active Contours and Level Sets: Application to Cerebrovascular Segmentation

  • Helena Molina-Abril
  • Alejandro F. Frangi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)

Abstract

One of the main problems of the existing methods for the segmentation of cerebral vasculature is the appearance in the segmentation result of wrong topological artefacts such as the kissing vessels. In this paper, a new approach for the detection and correction of such errors is presented. The proposed technique combines robust topological information given by Persistent Homology with complementary geometrical information of the vascular tree. The method was evaluated on 20 images depicting cerebral arteries. Detection and correction success rates were 81.80% and 68.77%, respectively.

Keywords

Simplicial Complex Segmentation Result Homology Group Homology Class Vascular Tree 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Helena Molina-Abril
    • 1
  • Alejandro F. Frangi
    • 1
  1. 1.Centre for Computational Imaging and Simulation Technologies in Biomedicine, Mechanical Engineering DepartmentUniversity of SheffieldUK

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