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A Fuzzy Connectivity Tree for Hierarchical Extraction of Venous Structures

  • Silvana Dellepiane
  • Lorena Novelli
  • Michele Bruzzo
  • Marco Antonelli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

In Magnetic Resonance Angiography (MRA), blood vessels show very high grey levels resulting from the use of a contrast agent. This leads to develop a formula, named β-connectedness, derived from fuzzy-connectedness theory [1],[2]. β-connectedness is described here as a specific case of more general χ-connectedness [3], for it allows one to improve the tracking of bright structures and, consequently, vessel extraction. In the computation of fuzzy connectedness, a widely used approach is based on an adaptive growing mechanism that follows the best paths starting from a reference seed point. As a consequence, a hierarchical tree is generated. Contrary to the aforesaid approach, here we propose to exploit such a tree information and we define the connectivity level as an additional parameter useful in the analysis of image data. The method presented in the paper deals with a new kind of connectivity that depends on the position of each pixel in the growing tree. The detection of fine structures is thus improved, as demonstrated by preliminary results on 3D MRA volumes.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Silvana Dellepiane
    • 1
  • Lorena Novelli
    • 1
  • Michele Bruzzo
    • 1
  • Marco Antonelli
    • 1
  1. 1.DIBE - Department of Biophysical and Electronic EngineeringUniversity of GenoaGenovaITALY

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