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Automatic detection of the intima-media thickness in ultrasound images of the common carotid artery using neural networks

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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.

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Acknowledgments

This work is partially supported by the Spanish Ministerio de Ciencia e Innovación, under Grant TEC2009-12675. The images used and the anatomical knowledge have been provided by the radiology department of Hospital Universitario Virgen de la Arrixaca, Murcia, Spain.

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Authors and Affiliations

  1. Departamento Tecnologías de la Información y las Comunicaciones, Universidad Politécnica de Cartagena, Plaza del Hospital, 1, 30202, Cartagena, Murcia, Spain

    Rosa-María Menchón-Lara, María-Consuelo Bastida-Jumilla, Juan Morales-Sánchez & José-Luis Sancho-Gómez

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  1. Rosa-María Menchón-Lara
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  2. María-Consuelo Bastida-Jumilla
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  3. Juan Morales-Sánchez
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Correspondence to Rosa-María Menchón-Lara.

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Menchón-Lara, RM., Bastida-Jumilla, MC., Morales-Sánchez, J. et al. Automatic detection of the intima-media thickness in ultrasound images of the common carotid artery using neural networks. Med Biol Eng Comput 52, 169–181 (2014). https://doi.org/10.1007/s11517-013-1128-4

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