Segmentation of carotid arteries in CTA images

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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
Pages69-74
Number of pages6
DOIs
Publication statusPublished - 2010
EventDigital Image Computing Techniques and Applications 2010 - Mercure Sydney Hotel, Sydney, Australia
Duration: 1 Dec 20103 Dec 2010
Conference number: 12

Conference

ConferenceDigital Image Computing Techniques and Applications 2010
Abbreviated titleDICTA 2010
CountryAustralia
CitySydney
Period1/12/103/12/10
Other(DICTA) is the main Australian conference on machine vision, image processing, pattern recognition and related areas. Since its establishment, DICTA has been a biannual meeting. In 2008, it turned into an annual conference. It is the conference of the Australian Pattern Recognition Society (APRS).

Keywords

  • Carotid artery
  • Watershed transform

Cite this

Beare, R., Chong, W., Ren, M., Das, G., Srikanth, V., & Phan, T. (2010). Segmentation of carotid arteries in CTA images. In Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010 (pp. 69-74). [5692542] https://doi.org/10.1109/DICTA.2010.21