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dc.contributor.authorLoizou, Christos P.en
dc.contributor.authorPantzaris, Marios C.en
dc.contributor.authorPattichis, Constantinos S.en
dc.creatorLoizou, Christos P.en
dc.creatorPantzaris, Marios C.en
dc.creatorPattichis, Constantinos S.en
dc.date.accessioned2019-11-13T10:41:04Z
dc.date.available2019-11-13T10:41:04Z
dc.date.issued2012
dc.identifier.isbn978-1-4614-1180-2
dc.identifier.isbn978-1-4614-1179-6
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54429
dc.description.abstractThe intima–media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator for the development of cardiovascular disease (CVD). It was proposed but not thoroughly investigated that the media layer (ML) thickness (MLT), its composition, and texture may be indicative of cardiovascular risk and for differentiating between patients with high and low risk. In this study, we investigate an automated snakes segmentation method for segmenting the ML and the intima layer (IL) and measurement of the MLT and the intima layer thickness (ILT) in ultrasound images of the CCA. We furthermore investigate the application of texture analysis of the ML of the CCA and how texture is affected by age and gender. The snakes segmentation method was used, and was evaluated on 100 longitudinal ultrasound images acquired from asymptomatic subjects, against manual segmentation performed by a neurovascular expert. The mean ± standard deviation (sd) for the first and second sets of manual and the automated IMT, MLT, and ILT measurements were 0. 71 ± 0. 17 mm, 0. 72 ± 0. 17 mm, 0. 67 ±0. 2 mm, 0. 25 ± 0. 12 mm, 0. 27 ± 0. 14, and 0. 25 ± 0. 11 mmen
dc.description.abstractand 0. 43 ±0. 10 mm, 0. 44 ± 0. 13 mm, and 0. 42 ± 0. 10 mm, respectively. There was overall no significant difference between the manual and the automated IMC, ML, and IL segmentation measurements. Therefore, the automated segmentation method proposed in this study may be used successfully in the measurement of the MLT and ILT complementing the manual measurements. MLT was also shown to increase with age (for both the manual and the automated measurements). Following the segmentation of the three structures, we also investigated the application of texture analysis of the ML of the CCA and how texture is affected by age and gender. The 100 images were separated into three different age groups, namely below 50, between 50 and 60, and above 60 years old. Furthermore, the images were separated according to gender. A total of 61 different texture features were extracted from the intima layer (IL), the ML, and the intima–media complex (IMC). We have found that male patients tended to have larger media layer thickness (MLT) values as compared to the MLT of female patients of the same age. We have also found significant differences among texture features extracted from the IL, ML, and IMC from different age groups. Furthermore, for some texture features, we found that they follow trends that correlate with a patient's age. For example, the gray-scale median GSM of the ML falls linearly with increasing MLT and with increasing age. Our findings suggest that ultrasound image texture analysis of the media layer has potential as an assessment biomarker for the risk of stroke. © Springer Science+Business Media, LLC 2012. All rights reserved.en
dc.publisherSpringer USen
dc.sourceUltrasound Imaging: Advances and Applicationsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84955698253&doi=10.1007%2f978-1-4614-1180-2_5&partnerID=40&md5=ffb5de3fc79c35fb6a2f475da0f238b0
dc.titleMedia and intima thickness and texture analysis of the common carotid Arteryen
dc.typeinfo:eu-repo/semantics/bookChapter
dc.description.startingpage99
dc.description.endingpage128
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeBook Chapteren
dc.contributor.orcidPattichis, Constantinos S. [0000-0003-1271-8151]
dc.contributor.orcidLoizou, Christos P. [0000-0003-1247-8573]
dc.contributor.orcidPantzaris, Marios C. [0000-0003-2937-384X]
dc.gnosis.orcid0000-0003-1271-8151
dc.gnosis.orcid0000-0003-1247-8573
dc.gnosis.orcid0000-0003-2937-384X


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