Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/23655
DC FieldValueLanguage
dc.contributor.authorLoizou, Christos P.-
dc.contributor.authorPattichis, Constantinos S.-
dc.contributor.authorChristodoulou, Christodoulos-
dc.contributor.authorIstepanian, Robert S H-
dc.contributor.authorPantziaris, Marios-
dc.contributor.authorNicolaides, Andrew N.-
dc.date.accessioned2021-11-17T09:18:08Z-
dc.date.available2021-11-17T09:18:08Z-
dc.date.issued2005-10-
dc.identifier.citationIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2005, vol. 52, no. 10, pp. 1653-1669en_US
dc.identifier.issn15258955-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/23655-
dc.description.abstractIt is well-known that speckle is a multiplicative noise that degrades the visual evaluation in ultrasound imaging. The recent advancements in ultrasound instrumentation and portable ultrasound devices necessitate the need of more robust despeckling techniques for enhanced ultrasound medical imaging for both routine clinical practice and teleconsultation. The objective of this work was to carry out a comparative evaluation of despeckle filtering based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts in the assessment of 440 (220 asymptomatic and 220 symptomatic) ultrasound images of the carotid artery bifurcation. In this paper a total of 10 despeckle filters were evaluated based on local statistics, median filtering, pixel homogeneity, geometric filtering, homomorphic filtering, anisotropic diffusion, nonlinear coherence diffusion, and wavelet filtering. The results of this study suggest that the first order statistics filter lsmv, gave the best performance, followed by the geometric filter gf4d, and the homogeneous mask area filter lsminsc. These filters improved the class separation between the asymptomatic and the symptomatic classes based on the statistics of the extracted texture features, gave only a marginal improvement in the classification success rate, and improved the visual assessment carried out by the two experts. More specifically, filters lsmv or gf4d can be used for despeckling asymptomatic images in which the expert is interested mainly in the plaque composition and texture analysis; and filters lsmv, gf4d, or lsminsc can be used for the despeckling of symptomatic images in which the expert is interested in identifying the degree of stenosis and the plaque borders. The proper selection of a despeckle filter is very important in the enhancement of ultrasonic imaging of the carotid artery. Further work is needed to evaluate at a larger scale and in clinical practice the performance of the proposed despeckle filters in the automated segmentation, texture analysis, and classification of carotid ultrasound imaging. © 2005 IEEE.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Controlen_US
dc.rights© IEEEen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectUltrasonic imagingen_US
dc.subjectBiomedical imagingen_US
dc.subjectImage texture analysisen_US
dc.subjectFiltersen_US
dc.subjectCarotid arteriesen_US
dc.subjectSpeckleen_US
dc.subjectDegradationen_US
dc.titleComparative evaluation of despeckle filtering in ultrasound imaging of the carotid arteryen_US
dc.typeArticleen_US
dc.collaborationIntercollegeen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationCyprus Institute of Neurology and Geneticsen_US
dc.collaborationImperial College Londonen_US
dc.collaborationKingston Universityen_US
dc.subject.categoryMedical Engineeringen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.countryUnited Kingdomen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1109/TUFFC.2005.1561621en_US
dc.identifier.pmid16382618-
dc.identifier.scopus2-s2.0-28444460771-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/28444460771-
dc.relation.issue10en_US
dc.relation.volume52en_US
cut.common.academicyear2005-2006en_US
dc.identifier.spage1653en_US
dc.identifier.epage1669en_US
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.fulltextNo Fulltext-
crisitem.journal.journalissn1525-8955-
crisitem.journal.publisherIEEE-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-1247-8573-
crisitem.author.parentorgFaculty of Engineering and Technology-
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