Segmentation of carotid arteries in CTA images

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

doi:10.1109/DICTA.2010.21

Segmentation of carotid arteries in CTA images

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

^*Corresponding author for this work

Faculty of Medicine, Health and Human Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

2 Citations (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 language	English
Title of host publication	Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010
Editors	Jian Zhang, Chunhua Shen, Glenn Geers
Place of Publication	Los Alamitos, CA
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	69-74
Number of pages	6
ISBN (Print)	9780769542713
DOIs	https://doi.org/10.1109/DICTA.2010.21
Publication status	Published - 2010
Event	International Conference on Digital Image Computing: Techniques and Applications, DICTA 2010 - Sydney, NSW, Australia Duration: 1 Dec 2010 → 3 Dec 2010

Other

Other	International Conference on Digital Image Computing: Techniques and Applications, DICTA 2010
Country/Territory	Australia
City	Sydney, NSW
Period	1/12/10 → 3/12/10

Keywords

Carotid artery
Watershed transform

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10.1109/DICTA.2010.21

Cite this

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title = "Segmentation of carotid arteries in CTA images",

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.",

keywords = "Carotid artery, Watershed transform",

author = "Richard Beare and Winston Chong and Mandy Ren and Gita Das and Velandai Srikanth and Thanh Phan",

year = "2010",

doi = "10.1109/DICTA.2010.21",

language = "English",

isbn = "9780769542713",

pages = "69--74",

editor = "Jian Zhang and Chunhua Shen and Glenn Geers",

booktitle = "Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "International Conference on Digital Image Computing: Techniques and Applications, DICTA 2010 ; Conference date: 01-12-2010 Through 03-12-2010",

}

Beare, R, Chong, W, Ren, M, Das, G, Srikanth, V & Phan, T 2010, Segmentation of carotid arteries in CTA images. in J Zhang, C Shen & G Geers (eds), Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010., 5692542, Institute of Electrical and Electronics Engineers (IEEE), Los Alamitos, CA, pp. 69-74, International Conference on Digital Image Computing: Techniques and Applications, DICTA 2010, Sydney, NSW, Australia, 1/12/10. https://doi.org/10.1109/DICTA.2010.21

Segmentation of carotid arteries in CTA images. / Beare, Richard; Chong, Winston; Ren, Mandy et al.

Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010. ed. / Jian Zhang; Chunhua Shen; Glenn Geers. Los Alamitos, CA : Institute of Electrical and Electronics Engineers (IEEE), 2010. p. 69-74 5692542.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Segmentation of carotid arteries in CTA images

AU - Beare, Richard

AU - Chong, Winston

AU - Ren, Mandy

AU - Das, Gita

AU - Srikanth, Velandai

AU - Phan, Thanh

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - Carotid artery

KW - Watershed transform

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SN - 9780769542713

SP - 69

EP - 74

BT - Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010

A2 - Zhang, Jian

A2 - Shen, Chunhua

A2 - Geers, Glenn

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Los Alamitos, CA

T2 - International Conference on Digital Image Computing: Techniques and Applications, DICTA 2010

Y2 - 1 December 2010 through 3 December 2010

ER -

Segmentation of carotid arteries in CTA images

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