Computer Aided Detection and Measurement of Peripheral Artery Disease.
Computer-Aided Tomography Angiography (CTA) images are the standard for assessing Peripheral artery disease (PAD). This paper presents a Computer Aided Detection (CAD) and Computer Aided Measurement (CAM) system for PAD. The CAD stage detects the arterial network using a 3D region growing method and...
| Publicado en: | Studies in Health Technology & Informatics Vol. 205; pp. 1153 - 1158 |
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| Autores principales: | , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2014
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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=116234759&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 116234759 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2014 vid: 205 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 116234759 116234759 116234759 10.3233/978-1-61499-432-9-1153 116234759 ppf: 1153 ppct: 5 formats: tig: atl: Computer Aided Detection and Measurement of Peripheral Artery Disease. aug: au: DEHMESHKI, Jamshid ION, Adina ELLIS, Tim DOENZ, Francesco JOUANNIC, Anne-Marie QANADLI, Salah affil: Quantitative Medical Imaging International Institutes (QMI3), Faculty of Science, Engineering and Computing, United Kingdom sug: subj: Computers and Computerization Weights and Measures Arteries Computer-Aided Design Disease ab: Computer-Aided Tomography Angiography (CTA) images are the standard for assessing Peripheral artery disease (PAD). This paper presents a Computer Aided Detection (CAD) and Computer Aided Measurement (CAM) system for PAD. The CAD stage detects the arterial network using a 3D region growing method and a fast 3D morphology operation. The CAM stage aims to accurately measure the artery diameters from the detected vessel centerline, compensating for the partial volume effect using Expectation Maximization (EM) and a Markov Random field (MRF). The system has been evaluated on phantom data and also applied to fifteen (15) CTA datasets, where the detection accuracy of stenosis was 88% and the measurement accuracy was with an 8% error. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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