dc.contributor.author | Kyriacou, Efthyvoulos C. | en |
dc.contributor.author | Pattichis, Marios S. | en |
dc.contributor.author | Christodoulou, Christodoulos I. | en |
dc.contributor.author | Pattichis, Constantinos S. | en |
dc.contributor.author | Kakkos, Stavros K. | en |
dc.contributor.author | Griffin, Maura B. | en |
dc.contributor.author | Nicolaïdes, Andrew N. | en |
dc.creator | Kyriacou, Efthyvoulos C. | en |
dc.creator | Pattichis, Marios S. | en |
dc.creator | Christodoulou, Christodoulos I. | en |
dc.creator | Pattichis, Constantinos S. | en |
dc.creator | Kakkos, Stavros K. | en |
dc.creator | Griffin, Maura B. | en |
dc.creator | Nicolaïdes, Andrew N. | en |
dc.date.accessioned | 2019-11-13T10:40:52Z | |
dc.date.available | 2019-11-13T10:40:52Z | |
dc.date.issued | 2005 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/54338 | |
dc.description.abstract | The aim of this chapter is to summarise the recent advances in ultrasonic plaque characterisation and to evaluate the efficacy of computer aided diagnosis based on neural and statistical classifiers using as input texture and morphological features. Several classifiers like the K-Nearest Neighbour (KNN) the Probabilistic Neural Network (PNN) and the Support Vecton Machine (SVM) are evaluated resulting to a diagnostic accuracy up to 71.2%. © 2005 The authors. All rights reserved. | en |
dc.source | Studies in health technology and informatics | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-34047169396&partnerID=40&md5=f30e27e69b335349dd7c4551fcfe979e | |
dc.subject | Algorithms | en |
dc.subject | human | en |
dc.subject | Humans | en |
dc.subject | algorithm | en |
dc.subject | ultrasound | en |
dc.subject | diagnostic imaging | en |
dc.subject | cerebrovascular accident | en |
dc.subject | Stroke | en |
dc.subject | artificial neural network | en |
dc.subject | Neural Networks (Computer) | en |
dc.subject | Ultrasonics | en |
dc.subject | computer assisted diagnosis | en |
dc.subject | texture analysis | en |
dc.subject | Diagnosis, Computer-Assisted | en |
dc.subject | assessment of stroke | en |
dc.subject | morphology analysis | en |
dc.subject | Ultrasound plaque image | en |
dc.title | Ultrasound imaging in the analysis of carotid plaque morphology for the assessment of stroke | en |
dc.type | info:eu-repo/semantics/article | |
dc.description.volume | 113 | |
dc.description.startingpage | 241 | |
dc.description.endingpage | 275 | |
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 :37</p> | en |
dc.source.abbreviation | Stud.Health Technol.Informatics | 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 | |