Automatic Ascending Aorta Detection in CTA Datasets

Saur, Stefan C. and Kühnel, Caroline and Boskamp, Tobias and Székely, Gábor and Cattin, Philippe. (2008) Automatic Ascending Aorta Detection in CTA Datasets. In: Bildverarbeitung für die Medizin 2008 : Algorithmen, Systeme, Anwendungen ; Proceedings des Workshops vom 6. bis 8. April 2008 in Berlin. Berlin, pp. 323-327.

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Official URL: http://edoc.unibas.ch/dok/A6308300

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The assessment of coronary arteries is an essential step when diagnosing coronary heart diseases. There exists a wide range of specialized algorithms for the segmentation of the coronary arteries in Computed Tomography Angiography datasets. In general, these algorithms have to be initialized by manually placing a seed point at the origins of the coronary arteries or within the ascending aorta. In this paper we present a fast and robust algorithm for the automatic detection of the ascending aorta in Computed Tomography Angiography datasets using a two-level threshold ray propagation approach. We further combine this method with an aorta segmentation and coronary artery tree detection algorithm to achieve a fully automatic coronary artery segmentation.
Faculties and Departments:03 Faculty of Medicine > Departement Biomedical Engineering > Imaging and Computational Modelling > Center for medical Image Analysis & Navigation (Cattin)
UniBasel Contributors:Cattin, Philippe Claude
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Series Name:Informatik aktuell
Note:Publication type according to Uni Basel Research Database: Conference paper
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Last Modified:29 Nov 2016 14:03
Deposited On:03 Jul 2015 08:53

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