Computer assisted matching of anatomical vessel trees

Cristina Oyarzun Laura, Klaus Drechsler

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Many inexact automatic tree matching algorithms are available. However, they provide matches that are not completely error free. Another option is to use manually matched node-pairs, but this enormously slows down the process. Our contribution to the state of the art is to combine the advantages of both solutions. We enhance the automatic tree matching algorithm designed by Graham et al., so that it is possible to interact with it by previously selecting important matches or by subsequently fixing the provided wrong matches. We apply the tree matching algorithm to the anatomical vasculature of the liver. Furthermore, we developed several visualization features to make manual tree interaction as easy as possible. Both, the interactive and automatic part of the implemented component were evaluated. As a result, the speed of the automatic tree matching algorithm is increased. It takes 7.45 s for trees up to 192 nodes and less than 1 s if three input matches are provided. In addition to this, an in-depth evaluation of the robustness of the algorithm is presented. The results are remarkable. The average of wrong matches varies between 1.17 and 1.4 node-pairs in the worst cases. The rate of correct matches is high. The evaluation of the visualization features for interactive refinement of matches showed that the percentage of wrong matches found is increased from 56.25% to 78.43%. The mean time to find them is decreased from 227 to 122 s.

Original languageEnglish
Pages (from-to)299-311
Number of pages13
JournalComputers and Graphics (Pergamon)
Volume35
Issue number2
DOIs
StatePublished - Apr 2011
Externally publishedYes

Keywords

  • Automatic
  • Graph matching
  • Interactive
  • Liver

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