Automatic Active Contour-Based Segmentation and Classification of Carotid Artery Ultrasound Images.
In this paper, we present automatic image segmentation and classification technique for carotid artery ultrasound images based on active contour approach. For early detection of the plaque in carotid artery to avoid serious brain strokes, active contour-based techniques have been applied successfull...
| Publicado en: | Journal of Digital Imaging Vol. 26; no. 6; pp. 1071 - 1082 |
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| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2013
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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=104153849&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104153849 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Dec2013 vid: 26 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104153849 91842812 10.1007/s10278-012-9566-3 NLM23417308 104153849 ppf: 1071 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Automatic Active Contour-Based Segmentation and Classification of Carotid Artery Ultrasound Images. aug: au: Chaudhry, Asmatullah Hassan, Mehdi Khan, Asifullah Kim, Jin affil: Pattern Recognition Lab, PIEAS, P.O. Nilore 45650 Islamabad Pakistan sug: subj: Carotid Arteries Ultrasonography Diagnostic Imaging Methods Diagnostic Imaging Evaluation Human Sensitivity and Specificity Research Methodology ab: In this paper, we present automatic image segmentation and classification technique for carotid artery ultrasound images based on active contour approach. For early detection of the plaque in carotid artery to avoid serious brain strokes, active contour-based techniques have been applied successfully to segment out the carotid artery ultrasound images. Further, ultrasound images might be affected due to rotation, scaling, or translational factors during acquisition process. Keeping in view these facts, image alignment is used as a preprocessing step to align the carotid artery ultrasound images. In our experimental study, we exploit intima-media thickness (IMT) measurement to detect the presence of plaque in the artery. Support vector machine (SVM) classification is employed using these segmented images to distinguish the normal and diseased artery images. IMT measurement is used to form the feature vector. Our proposed approach segments the carotid artery images in an automatic way and further classifies them using SVM. Experimental results show the learning capability of SVM classifier and validate the usefulness of our proposed approach. Further, the proposed approach needs minimum interaction from a user for an early detection of plaque in carotid artery. Regarding the usefulness of the proposed approach in healthcare, it can be effectively used in remote areas as a preliminary clinical step even in the absence of highly skilled radiologists. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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