Automatic detection of the intima-media thickness in ultrasound images of the common carotid artery using neural networks.
Atherosclerosis is the leading underlying pathologic process that results in cardiovascular diseases, which represents the main cause of death and disability in the world. The atherosclerotic process is a complex degenerative condition mainly affecting the medium- and large-size arteries, which begi...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 52; no. 2; pp. 169 - 182 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Feb2014
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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=104010956&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104010956 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Feb2014 vid: 52 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104010956 NLM24281725 2012455926 10.1007/s11517-013-1128-4 NLM24281725 104010956 ppf: 169 ppct: 13 formats: fmt: @attributes: type: P tig: atl: Automatic detection of the intima-media thickness in ultrasound images of the common carotid artery using neural networks. aug: au: Menchón-Lara, Rosa-María Bastida-Jumilla, María-Consuelo Morales-Sánchez, Juan Sancho-Gómez, José-Luis affil: Departamento Tecnologías de la Información y las Comunicaciones, Universidad Politécnica de Cartagena, Plaza del Hospital, 1, 30202, Cartagena, Murcia, Spain, rmml@alu.upct.es. sug: subj: Atherosclerosis Ultrasonography Carotid Arteries Ultrasonography Carotid Intima-Media Thickness Neural Networks (Computer) Adult Aged Algorithms Female Image Processing, Computer Assisted Male Middle Age Adult: 19-44 years Aged: 65+ years Middle Aged: 45-64 years Female Male ab: Atherosclerosis is the leading underlying pathologic process that results in cardiovascular diseases, which represents the main cause of death and disability in the world. The atherosclerotic process is a complex degenerative condition mainly affecting the medium- and large-size arteries, which begins in childhood and may remain unnoticed during decades. The intima-media thickness (IMT) of the common carotid artery (CCA) has emerged as one of the most powerful tool for the evaluation of preclinical atherosclerosis. IMT is measured by means of B-mode ultrasound images, which is a non-invasive and relatively low-cost technique. This paper proposes an effective image segmentation method for the IMT measurement in an automatic way. With this purpose, segmentation is posed as a pattern recognition problem, and a combination of artificial neural networks has been trained to solve this task. In particular, multi-layer perceptrons trained under the scaled conjugate gradient algorithm have been used. The suggested approach is tested on a set of 60 longitudinal ultrasound images of the CCA by comparing the automatic segmentation with four manual tracings. Moreover, the intra- and inter-observer errors have also been assessed. Despite of the simplicity of our approach, several quantitative statistical evaluations have shown its accuracy and robustness. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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