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dc.contributor.authorLoizou, Christos P.en
dc.contributor.authorMurray, V.en
dc.contributor.authorPattichis, Marios S.en
dc.contributor.authorPantzaris, Marios C.en
dc.contributor.authorNicolaïdes, Andrew N.en
dc.contributor.authorPattichis, Constantinos S.en
dc.creatorLoizou, Christos P.en
dc.creatorMurray, V.en
dc.creatorPattichis, Marios S.en
dc.creatorPantzaris, Marios C.en
dc.creatorNicolaïdes, Andrew N.en
dc.creatorPattichis, Constantinos S.en
dc.date.accessioned2019-11-13T10:41:02Z
dc.date.available2019-11-13T10:41:02Z
dc.date.issued2014
dc.identifier.issn1687-4188
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54421
dc.description.abstractThe intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of cardiovascular disease (CVD). Typically, the IMT grows with age and this is used as a sign of increased risk of CVD. Beyond thickness, there is also clinical interest in identifying how the composition and texture of the intima-media complex (IMC) changed and how these textural changes grow into atherosclerotic plaques that can cause stroke. Clearly though texture analysis of ultrasound images can be greatly affected by speckle noise, our goal here is to develop effective despeckle noise methods that can recover image texture associated with increased rates of atherosclerosis disease. In this study, we perform a comparative evaluation of several despeckle filtering methods, on 100 ultrasound images of the CCA, based on the extracted multiscale Amplitude-Modulation Frequency-Modulation (AM-FM) texture features and visual image quality assessment by two clinical experts. Texture features were extracted from the automatically segmented IMC for three different age groups. The despeckle filters hybrid median and the homogeneous mask area filter showed the best performance by improving the class separation between the three age groups and also yielded significantly improved image quality. © 2014 C. P. Loizou et al.en
dc.sourceInternational Journal of Biomedical Imagingen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84897545511&doi=10.1155%2f2014%2f518414&partnerID=40&md5=f09119579a16693feb9a45a5acf0e704
dc.subjectarticleen
dc.subjecthumanen
dc.subjectadulten
dc.subjectcontrolled studyen
dc.subjectfemaleen
dc.subjectmajor clinical studyen
dc.subjectCardiovascular diseaseen
dc.subjectmaleen
dc.subjectgroups by ageen
dc.subjectimage analysisen
dc.subjectquality controlen
dc.subjectfrequency modulationen
dc.subjectDiseasesen
dc.subjectUltrasonicsen
dc.subjectarterial wall thicknessen
dc.subjectTexturesen
dc.subjectCommon carotid arteryen
dc.subjectComparative evaluationsen
dc.subjectAmplitude modulationen
dc.subjectUltrasound imagesen
dc.subjectcarotid atherosclerosisen
dc.subjectAtherosclerotic plaqueen
dc.subjectImage qualityen
dc.subjectIntima-media thicknessen
dc.subjectFiltering methoden
dc.subjectMedian filtersen
dc.subjectClass separationen
dc.subjectImage textureen
dc.subjectretina imageen
dc.subjectultrasound scanneren
dc.titleDespeckle filtering for multiscale amplitude-modulation frequency-modulation (AM-FM) texture analysis of ultrasound images of the intima-media complexen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1155/2014/518414
dc.description.volume2014
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.description.notes<p>Tradenames: ATL HDI-3000, Advanced Technology, United Statesen
dc.description.notesManufacturers: Advanced Technology, United Statesen
dc.description.notesCited By :6</p>en
dc.source.abbreviationInt.J.Biomed.Imagingen
dc.contributor.orcidPattichis, Constantinos S. [0000-0003-1271-8151]
dc.contributor.orcidPattichis, Marios S. [0000-0002-1574-1827]
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.orcid0000-0002-1574-1827
dc.gnosis.orcid0000-0003-1247-8573
dc.gnosis.orcid0000-0003-2937-384X


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