Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/7052
Title: Full-automated system for the segmentation of the common carotid artery in ultrasound images
Authors: Kasparis, Takis 
Loizou, Christos P. 
Christodoulou, Lakis
Keywords: Adaptive filters
Carotid artery
Ultrasonic imaging
Diagnostic imaging
Image processing
Issue Date: 2012
Publisher: IEEE
Source: 5th International Symposium on Communications Control and Signal Processing ISCCSP, 2012, Article number 6217824, Pages 1- 6
Abstract: The full segmentation of the common carotid artery (CCA) in ultrasound images is important for the evaluation of the intima media thickness (IMT) and for the measurement of the artery stenosis which are considered to be the significant markers for the clinical evaluation of the risk of stroke. The current research proposes full-automated segmentation system for the segmentation of the CCA, which is based on an adaptive snake-contour segmentation algorithm. The CCA is segmented by the proposed algorithm into different distinct regions, namely the IMT, intima-media (IL), media-layer (ML), carotid plaque and lumen. The proposed method is automatically processing image normalization, binarization, adaptive hybrid median filter, and morphology prior the application of the snake segmentation algorithm. The mean and standard deviation of the IMT diameter in y-axis of the full-automatically segmented regions for the snakes-based and level-set method are 0.12 mm/0.01 mm and 0.09 mm/0.01 mm respectively in comparison with the ground truth IMT extracted from the manual clinical segmentation. The Wilcoxon rank sum test shows the significant improvements of the proposed method.
URI: http://ktisis.cut.ac.cy/handle/10488/7052
ISBN: 978-1-4673-0274-6
DOI: 10.1109/ISCCSP.2012.6217824
Rights: © 2012 IEEE
Appears in Collections:Κεφάλαια βιβλίων/Book chapters

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