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https://hdl.handle.net/20.500.14279/23593
Πεδίο DC | Τιμή | Γλώσσα |
---|---|---|
dc.contributor.author | Loizou, Christos P. | - |
dc.contributor.author | Pantzaris, Marios C. | - |
dc.date.accessioned | 2021-11-09T10:10:45Z | - |
dc.date.available | 2021-11-09T10:10:45Z | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | Multi-Modality Atherosclerosis Imaging and Diagnosis, 2014, pp. 237-246 | en_US |
dc.identifier.isbn | 978-1-4614-7425-8 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/23593 | - |
dc.description.abstract | In this chapter, we propose and evaluate an integrated system for the segmentation of atherosclerotic plaque in ultrasound imaging of the carotid artery based on normalization, speckle reduction filtering, and four different snakes segmentation methods. These methods are the Williams and Shah, Balloon, Lai and Chin, and the gradient vector flow (GVF) snake. The performance of the four different plaque snakes segmentation methods was tested on 80 longitudinal ultrasound images of the carotid artery using receiver operating characteristic (ROC) analysis and the manual delineations of an expert. All four methods performed very satisfactorily and similarly in all measures evaluated with no significant differences between them; however, the Lai and Chin snakes segmentation method gave slightly better results. Concluding, it is proposed that the integrated system investigated in this study could be used successfully for the automated segmentation of the carotid plaque. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.rights | © Springer | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Carotid Artery | en_US |
dc.subject | Ultrasound Image | en_US |
dc.subject | Segmentation Method | en_US |
dc.subject | Carotid Plaque | en_US |
dc.subject | IVUS Image | en_US |
dc.title | Atherosclerotic carotid plaque segmentation in ultrasound imaging of the carotid artery | en_US |
dc.type | Book Chapter | en_US |
dc.collaboration | Intercollege | en_US |
dc.collaboration | Cyprus Institute of Neurology and Genetics | en_US |
dc.subject.category | Medical Engineering | en_US |
dc.country | Cyprus | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1007/978-1-4614-7425-8_19 | en_US |
dc.identifier.scopus | 2-s2.0-84929537491 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/84929537491 | - |
cut.common.academicyear | 2013-2014 | en_US |
dc.identifier.spage | 237 | en_US |
dc.identifier.epage | 246 | en_US |
item.grantfulltext | none | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_3248 | - |
item.openairetype | bookPart | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0003-1247-8573 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Εμφανίζεται στις συλλογές: | Κεφάλαια βιβλίων/Book chapters |
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