A hybrid plaque characterization method using intravascular ultrasound images.
Background: Intravascular ultrasound (IVUS) is an invasive imaging modality that provides high resolution cross-sectional images permitting detailed evaluation of the lumen, outer vessel wall and plaque morphology and evaluation of its composition. Over the last years several methodologies have been...
| Publicado en: | Technology & Health Care Vol. 21; no. 1; pp. 199 - 217 |
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| Autores principales: | , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Sage Publications Inc.
2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104035886&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104035886 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09287329 3QT jtl: Technology & Health Care issn: 09287329 maglogo: N pubinfo: dt: 2013 vid: 21 iid: 1 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 104035886 104035886 NLM23792794 2012280679 10.3233/THC-130717 NLM23792794 104035886 ppf: 199 ppct: 18 formats: tig: atl: A hybrid plaque characterization method using intravascular ultrasound images. aug: au: Athanasiou, Lambros S Karvelis, Petros S Sakellarios, Antonis I Exarchos, Themis P Siogkas, Panagiotis K Tsakanikas, Vassilis D Naka, Katerina K Bourantas, Christos V Papafaklis, Michail I Koutsouri, Georgia Michalis, Lampros K Parodi, Oberdan Fotiadis, Dimitrios I affil: Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece. sug: subj: Image Processing, Computer Assisted Methods Atherosclerosis Classification Atherosclerosis Ultrasonography Ultrasonography Methods Algorithms Human Reproducibility of Results ab: Background: Intravascular ultrasound (IVUS) is an invasive imaging modality that provides high resolution cross-sectional images permitting detailed evaluation of the lumen, outer vessel wall and plaque morphology and evaluation of its composition. Over the last years several methodologies have been proposed which allow automated processing of the IVUS data and reliable segmentation of the regions of interest or characterization of the type of the plaque. Objective: In this paper we present a novel methodology for the automated identification of different plaque components in grayscale IVUS images. Methods: The proposed method is based on a hybrid approach that incorporates both image processing techniques and classification algorithms and allows classification of the plaque into three different categories: Hard Calcified, Hard-Non Calcified and Soft plaque. Annotations by two experts on 8 IVUS examinations were used to train and test our method. Results: The combination of an automatic thresholding technique and active contours coupled with a Random Forest classifier provided reliable results with an overall classification accuracy of 86.14%. Conclusions: The proposed method can accurately detect the plaque using grayscale IVUS images and can be used to assess plaque composition for both clinical and research purposes. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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