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Coronary artery segmentation and skeletonization based on competing fuzzy connectedness tree
Linköping University Hospital.ORCID iD: 0000-0002-0442-3524
Linköping University Hospital.ORCID iD: 0000-0002-7750-1917
2007 (English)In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007, Berlin, Heidelberg, 2007, p. 311-318Conference paper, Published paper (Refereed)
Abstract [en]

We propose a new segmentation algorithm based on competing fuzzy connectedness theory, which is then used for visualizing coronary arteries in 3D CT angiography (CTA) images. The major difference compared to other fuzzy connectedness algorithms is that an additional data structure, the connectedness tree, is constructed at the same time as the seeds propagate. In preliminary evaluations, accurate result have been achieved with very limited user interaction. In addition to improving computational speed and segmentation results, the fuzzy connectedness tree algorithm also includes automated extraction of the vessel centerlines, which is a promising approach for creating curved plane reformat (CPR) images along arteries’ long axes.

Place, publisher, year, edition, pages
Berlin, Heidelberg, 2007. p. 311-318
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 4791
Keywords [en]
Segmentation, fuzzy connectedness tree, centerline extraction, skeletonization, coronary artery, CT angiography
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:kth:diva-258839DOI: 10.1007/978-3-540-75757-3_38ISI: 000250916000038Scopus ID: 2-s2.0-79551684063ISBN: 978-3-540-75756-6 (print)ISBN: 978-3-540-75757-3 (electronic)OAI: oai:DiVA.org:kth-258839DiVA, id: diva2:1350283
Conference
International Conference on Medical Image Computing and Computer-Assisted Intervention
Note

QC 20191030

Available from: 2019-09-11 Created: 2019-09-11 Last updated: 2019-10-30Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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