Efficient Globally Optimal Matching of Anatomical Trees of the Liver

dc.contributor.authorLaura, Cristina Oyarzunen_US
dc.contributor.authorDrechsler, Klausen_US
dc.contributor.editorDirk Bartz and Charl Botha and Joachim Hornegger and Raghu Machiraju and Alexander Wiebel and Bernhard Preimen_US
dc.date.accessioned2014-01-29T17:09:02Z
dc.date.available2014-01-29T17:09:02Z
dc.date.issued2010en_US
dc.description.abstractMany inexact automatic tree matching algorithms are nowadays 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. Thanks to this enhancement the speed of the algorithm is greatly increased. It takes 7.45 seconds for trees up to 192 nodes and less than 1 second 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.en_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicineen_US
dc.identifier.isbn978-3-905674-28-6en_US
dc.identifier.issn2070-5786en_US
dc.identifier.urihttps://doi.org/10.2312/VCBM/VCBM10/075-082en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): G.2.2 [Discrete Mathematics]: Graph Algorithms; I.5.3 [Pattern recognition]: Similarity measures; I.4.3 [Image Processing and Computer Vision]: Registrationen_US
dc.titleEfficient Globally Optimal Matching of Anatomical Trees of the Liveren_US
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