Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/9790
Title: | Integrated system for the complete segmentation of the common carotid artery bifurcation in ultrasound images | Authors: | Loizou, Christos P. Kasparis, Takis Spyrou, Christina Pantziaris, Marios |
Major Field of Science: | Engineering and Technology;Medical and Health Sciences | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering;MEDICAL AND HEALTH SCIENCES;Clinical Medicine | Keywords: | Atherosclerotic plaque;Carotid artery;Carotid segmentation;Ultrasound image;Intima-media thickness;Lumen diameter | Issue Date: | Dec-2013 | Source: | 9th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, 2013, Paphos, Cyprus | Conference: | IFIP Advances in Information and Communication Technology | Abstract: | The complete segmentation of the common carotid artery (CCA) bifurcation in ultrasound images is important for the evaluation of atherosclerosis disease and the quantification of the risk of stroke. This requires the extraction of the intima-media complex (IMC), the delineation of the lumen the atherosclerotic carotid plaque and measurement of the artery stenosis. The current research proposes an automated segmentation system for the complete segmentation of the CCA bifurcation in ultrasound images, which is based on snakes. The algorithm was evaluated on 20 longitudinal ultrasound images of the CCA bifurcation with manual segmentations available from a neurovascular expert. The manual mean±SD measurements were for the IMT: (0.96±0.22) mm, lumen diameter: (5.59±0.84) mm and ICA origin stenosis (48.1±11.52) %, while the automated measurements were for the IMT: (0.93±0.22) mm, lumen diameter: (5.77±0.99) mm and ICA stenosis (51.05±14.51) % respectively. We found no significant differences between all manual and the automated segmentation measurements. | Description: | Originally published with the title: IFIP International Federation for Information Processing | ISBN: | 978-364241141-0 | DOI: | 10.1007/978-3-642-41142-7_30 | Rights: | © IFIP International Federation for Information Processing 2013. | Type: | Conference Papers | Affiliation : | Cyprus University of Technology Cyprus Institute of Neurology and Genetics |
Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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