Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Integrating automatic and interactive methods for coronary artery segmentation: let the PACS workstation think ahead
Linköping University, Linköping, Sweden.ORCID iD: 0000-0002-0442-3524
Linköping University, Linköping, Sweden.ORCID iD: 0000-0002-7750-1917
2010 (English)In: International Journal of Computer Assisted Radiology and Surgery, ISSN 1861-6410, E-ISSN 1861-6429, Vol. 5, no 3, p. 275-285Article in journal (Refereed) Published
Abstract [en]

Purpose To present newly developed software that can provide fast coronary artery segmentation and accurate centerline extraction for later lesion visualization and quantitative measurement while minimizing user interaction. Methods Previously reported fully automatic and interactive methods for coronary artery extraction were optimized and integrated into a user-friendly workflow. The user's waiting time is saved by running the non-supervised coronary artery segmentation and centerline tracking in the background as soon as the images are received. When the user opens the data, the software provides an intuitive interactive analysis environment. Results The average overlap between the centerline created in our software and the reference standard was 96.0%. The average distance between them was 0.38 mm. The automatic procedure runs for 1.4-2.5 min as a single-thread application in the background. Interactive processing takes 3 min in average. Conclusion In preliminary experiments, the software achieved higher efficiency than the former interactive method, and reasonable accuracy compared to manual vessel extraction.

Place, publisher, year, edition, pages
Springer, 2010. Vol. 5, no 3, p. 275-285
Keywords [en]
Coronary CT angiography; Automatic vessel extraction; Vessel segmentation; Centerline tracking
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:kth:diva-258842DOI: 10.1007/s11548-009-0393-zISI: 000289288800008PubMedID: 20033501Scopus ID: 2-s2.0-77953612020OAI: oai:DiVA.org:kth-258842DiVA, id: diva2:1350276
Note

QC 20190911

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

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Authority records BETA

Smedby, Örjan

Search in DiVA

By author/editor
Wang, ChunliangSmedby, Örjan
In the same journal
International Journal of Computer Assisted Radiology and Surgery
Medical Image Processing

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 17 hits
CiteExportLink to record
Permanent link

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