2026-04-14T18:44:40Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/658752025-02-19T13:00:45Zcom_10324_1191com_10324_931com_10324_894col_10324_1379
Menchon Lara, Rosa María
Bastida Jumilla, María Consuelo
Morales Sánchez, Juan
Sancho Gómez, José Luis
2024-02-07T08:44:39Z
2024-02-07T08:44:39Z
2013
Med Biol Eng Comput, 52, 169–181 (2014)
0140-0118
https://uvadoc.uva.es/handle/10324/65875
10.1007/s11517-013-1128-4
169
2
181
Medical & Biological Engineering & Computing
52
1741-0444
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.
eng
info:eu-repo/semantics/restrictedAccess
Automatic detection of the intima-media thickness in ultrasound images of the common carotid artery using neural networks
info:eu-repo/semantics/article