Automated Slice-Based Artery Identification in Various Field-of-View CTA Scans

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dc.contributor.authorMajor, Daviden_US
dc.contributor.authorNovikov, Alexey A.en_US
dc.contributor.authorWimmer, Mariaen_US
dc.contributor.authorHladuvka, Jirien_US
dc.contributor.authorBühler, Katjaen_US
dc.contributor.editorKatja Bühler and Lars Linsen and Nigel W. Johnen_US
dc.date.accessioned2015-09-14T04:49:02Z
dc.date.available2015-09-14T04:49:02Z
dc.date.issued2015en_US
dc.description.abstractAutomated identification of main arteries in Computed Tomography Angiography (CTA) scans plays a key role in the initialization of vessel tracking algorithms. Automated vessel tracking tools support physicians in vessel analysis and make their workflow time-efficient. We present a fully-automated framework for identification of five main arteries of three different body regions in various field-of-view CTA scans. Our method detects the two common iliac arteries, the aorta and the two common carotid arteries and delivers seed positions in them. After the field-of-view of a CTA scan is identified, artery candidate positions are regressed slice-wise and the best candidates are selected by Naive Bayes classification. Final artery seed positions are detected by picking the most optimal path over the artery classification results from slice to slice. Our method was evaluated on 20 CTA scans with various field-of-views. The high detection performance on different arteries shows its generality and future applicability for automated vessel analysis systems.en_US
dc.description.sectionheadersVisual Computing for Vessel Structuresen_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicineen_US
dc.identifier.doi10.2312/vcbm.20151215en_US
dc.identifier.isbn978-3-905674-82-8en_US
dc.identifier.issn2070-5786en_US
dc.identifier.pages123-129en_US
dc.identifier.urihttps://doi.org/10.2312/vcbm.20151215en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.4.8 [Image Processing and Computer Vision]en_US
dc.subjectScene Analysisen_US
dc.subjectObject recognitionen_US
dc.titleAutomated Slice-Based Artery Identification in Various Field-of-View CTA Scansen_US
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VCBM 15: Eurographics Workshop on Visual Computing for Biology and Medicine