Segmentation of carotid arteries in CTA images

Richard Beare*, Winston Chong, Mandy Ren, Gita Das, Velandai Srikanth, Thanh Phan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

Stenosis of the internal carotid artery (ICA) is implicated in approximately one quarter of stroke cases. The degree of stenosis is currently used to decide whether to undertake a surgical procedure to reduce the risk of further stroke. However it is known that the degree of stenosis is not a good predictor of stroke risk. It is hoped that prediction might be improved by incorporation of other geometric factors. This paper describes a data driven approach using classical methods from the field of mathematical morphology to automatically segment the carotid artery tree in computed tomography angiography (CTA) images following user initialization. The resulting segmentation may be used to characterize the the arterial geometery in a variety of more complex ways than is possible using manual approaches.

Original languageEnglish
Title of host publicationProceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010
EditorsJian Zhang, Chunhua Shen, Glenn Geers
Place of PublicationLos Alamitos, CA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages69-74
Number of pages6
ISBN (Print)9780769542713
DOIs
Publication statusPublished - 2010
EventInternational Conference on Digital Image Computing: Techniques and Applications, DICTA 2010 - Sydney, NSW, Australia
Duration: 1 Dec 20103 Dec 2010

Other

OtherInternational Conference on Digital Image Computing: Techniques and Applications, DICTA 2010
CountryAustralia
CitySydney, NSW
Period1/12/103/12/10

Keywords

  • Carotid artery
  • Watershed transform

Fingerprint Dive into the research topics of 'Segmentation of carotid arteries in CTA images'. Together they form a unique fingerprint.

Cite this