title: Automatic detection of the intima-media thickness in ultrasound images of the common carotid artery using neural networks.
abstract: 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.
authors.affiliation: Departamento Tecnologías de la Información y las Comunicaciones, Universidad Politécnica de Cartagena, Plaza del Hospital, 1, 30202, Cartagena, Murcia, Spain, rmml@alu.upct.es.
authors.forename: Rosa-María
authors.initials: RM
authors.lastname: Menchón-Lara
authors.forename: María-Consuelo
authors.initials: MC
authors.lastname: Bastida-Jumilla
authors.forename: Juan
authors.initials: J
authors.lastname: Morales-Sánchez
authors.forename: José-Luis
authors.initials: JL
authors.lastname: Sancho-Gómez
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D050197:Atherosclerosis / Q000000981:diagnostic imaging*; D017536:Carotid Artery, Common / Q000000981:diagnostic imaging*; D059168:Carotid Intima-Media Thickness; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer