An automatic branch and stenoses detection in computed tomography angiography

Suheyla Cetin*, Gozde Unal, Muzaffer Degertekin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this work, we present an automatic branch and stenoses detection method that is capable of detecting all types of plaques in Computed Tomography Angiography (CTA) modality. Our method is based on the vessel extraction algorithm we proposed in [1], and detects branches and stenoses in a very fast way. We demonstrate the performance of our branch detection method on 3 complex tubular structured synthetic datasets for quantitative validation. Additionally, we show the preliminary results of stenoses detection algorithm on 11 CTA volumes, which are qualitatively evaluated by a cardiologist expert.

Original languageEnglish
Title of host publication2012 9th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2012 - Proceedings
Pages582-585
Number of pages4
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Barcelona, Spain
Duration: 2 May 20125 May 2012

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012
Country/TerritorySpain
CityBarcelona
Period2/05/125/05/12

Keywords

  • branch detection
  • coronary arteries
  • CTA
  • segmentation
  • stenosis detection
  • tubular structures
  • vessel trees

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