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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