dc.contributor.author | Kyriacou, Efthyvoulos C. | en |
dc.contributor.author | Petroudi, Styliani | en |
dc.contributor.author | Pattichis, Constantinos S. | en |
dc.contributor.author | Pattichis, Marios S. | en |
dc.contributor.author | Griffin, Maura B. | en |
dc.contributor.author | Kakkos, Stavros K. | en |
dc.contributor.author | Nicolaïdes, Andrew N. | en |
dc.creator | Kyriacou, Efthyvoulos C. | en |
dc.creator | Petroudi, Styliani | en |
dc.creator | Pattichis, Constantinos S. | en |
dc.creator | Pattichis, Marios S. | en |
dc.creator | Griffin, Maura B. | en |
dc.creator | Kakkos, Stavros K. | en |
dc.creator | Nicolaïdes, Andrew N. | en |
dc.date.accessioned | 2019-11-13T10:40:53Z | |
dc.date.available | 2019-11-13T10:40:53Z | |
dc.date.issued | 2012 | |
dc.identifier.issn | 1089-7771 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/54343 | |
dc.description.abstract | Carotid plaques have been associated with ipsilateral neurological symptoms. High-resolution ultrasound can provide information not only on the degree of carotid artery stenosis but also on the characteristics of the arterial wall including the size and consistency of atherosclerotic plaques. The aim of this study is to determine whether the addition of ultrasonic plaque texture features to clinical features in patients with asymptomatic internal carotid artery stenosis (ACS) improves the ability to identify plaques that will produce stroke. 1121 patients with ACS have been scanned with ultrasound and followed for a mean of 4 years. It is shown that the combination of texture features based on second-order statistics spatial gray level dependence matrices (SGLDM) and clinical factors improves stroke prediction (by correctly predicting 89 out of the 108 cases that were symptomatic). Here, the best classification results of $77 \pm 1.8\%$ were obtained from the use of the SGLDM texture features with support vector machine classifiers. The combination of morphological features with clinical features gave slightly worse classification results of $76 \pm 2.6\%$. These findings need to be further validated in additional prospective studies. © 2012 IEEE. | en |
dc.source | IEEE Transactions on Information Technology in Biomedicine | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866598909&doi=10.1109%2fTITB.2012.2192446&partnerID=40&md5=cf320f75afbb00a2f350e4742da30626 | |
dc.subject | article | en |
dc.subject | Forecasting | en |
dc.subject | human | en |
dc.subject | Humans | en |
dc.subject | adult | en |
dc.subject | aged | en |
dc.subject | female | en |
dc.subject | male | en |
dc.subject | risk assessment | en |
dc.subject | pathology | en |
dc.subject | middle aged | en |
dc.subject | asymptomatic disease | en |
dc.subject | analysis of variance | en |
dc.subject | sensitivity and specificity | en |
dc.subject | echography | en |
dc.subject | cerebrovascular accident | en |
dc.subject | Stroke | en |
dc.subject | Ultrasonic imaging | en |
dc.subject | Ultrasonics | en |
dc.subject | High resolution | en |
dc.subject | Aged, 80 and over | en |
dc.subject | support vector machine | en |
dc.subject | Textures | en |
dc.subject | Morphological features | en |
dc.subject | Hemodynamics | en |
dc.subject | Internal carotid artery | en |
dc.subject | Carotid plaques | en |
dc.subject | Texture features | en |
dc.subject | Ultrasound images | en |
dc.subject | carotid artery obstruction | en |
dc.subject | Carotid Stenosis | en |
dc.subject | Atherosclerotic plaque | en |
dc.subject | Arterial wall | en |
dc.subject | Carotid artery stenosis | en |
dc.subject | Clinical features | en |
dc.subject | Neurological symptoms | en |
dc.subject | Prospective study | en |
dc.subject | plaque imaging | en |
dc.subject | Classification results | en |
dc.subject | Assessment of stroke risk | en |
dc.subject | Asymptomatic Diseases | en |
dc.subject | Gray levels | en |
dc.subject | Second order statistics | en |
dc.subject | Support Vector Machines | en |
dc.subject | Ultrasonic images | en |
dc.subject | ultrasound image analysis | en |
dc.title | Prediction of high-risk asymptomatic carotid plaques based on ultrasonic image features | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1109/TITB.2012.2192446 | |
dc.description.volume | 16 | |
dc.description.issue | 5 | |
dc.description.startingpage | 966 | |
dc.description.endingpage | 973 | |
dc.author.faculty | 002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Πληροφορικής / Department of Computer Science | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Cited By :24</p> | en |
dc.source.abbreviation | IEEE Trans.Inf.Technol.Biomed. | en |
dc.contributor.orcid | Pattichis, Constantinos S. [0000-0003-1271-8151] | |
dc.contributor.orcid | Pattichis, Marios S. [0000-0002-1574-1827] | |
dc.contributor.orcid | Kyriacou, Efthyvoulos C. [0000-0002-4589-519X] | |
dc.gnosis.orcid | 0000-0003-1271-8151 | |
dc.gnosis.orcid | 0000-0002-1574-1827 | |
dc.gnosis.orcid | 0000-0002-4589-519X | |