Abstract
Atherosclerosis is a cardiovascular disease very widespread into population. The intima-media thickness (IMT) is a reliable early indicator of this pathology. The IMT is measured by the doctor using images acquired with a B-scan ultrasound and this fact presents several problems. Image segmentation can detect the IMT throughout the artery length in an automatic way. This paper presents an effective segmentation method based on the use of a neural network ensemble. The obtained results show the ability of the method to extract the IMT contour in ultrasound images.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bankman, I.N.: Handbook of Medical Imaging: Processing and Analysis. Academic Press, London (2000)
Burke, G.L., Evans, G.W., Riley, W.A., Sharrett, A.R., Howard, G., Barnes, R.W., Rosamond, W., Crow, R.S., Rautaharju, P.M., Heiss, G.: Arterial wall thickness is associated with prevalent cardiovascular disease in middle-aged adults. Stroke 26(3), 386–391 (1995)
Giacinto, G., Roli, F.: Desing of effective neural network ensembles for image classification purposes. Image and Vision Computing 19, 699–707 (2001)
Haykin, S.: Neural Networks: A Comprehensive Foundation. Prentice-Hall, Englewood Cliffs (1999)
Izquierdo-Zaragoza, J.L., Consuelo Bastida-Jumilla, M., Verdú-Monedero, R., Morales-Sánchez, J., Berenguer-Vidal, R.: Segmentation of the carotid artery in ultrasound images using frequency-designed b-spline active contour. In: International Conference on Acoustics, Speech and Signal Processing (2011)
Ceccarelli, M., Luca, N.D., Morganella, A.: An active contour approach to automatic detection of the intima-media thickness. In: IEEE Int Conf. Acoustics, Speech and Signal Processing (2006)
Meyer-Base, A.: Pattern Recognition for Medical Imaging. Academic Press, London (2004)
Moller, M.F.: A scaled conjugate gradient algorithm for fast supervised learning. Neural Networks 6, 525–533 (1993)
Liang, Q., Wendelhag, I., Wikstrand, J., Gustavsson, T.: A multiscale dynamic programming procedure for boundary detection in ultrasonic artery images. IEEE Trans. on Medical Imaging 19(2), 127–142 (2000)
González, R.C., Woods, R.E.: Digital Image Processing. Prentice-Hall, Englewood Cliffs (2002)
Rocha, R., Campilho, A., Silva, J., Azevedo, E., Santos, R.: Segmentation of the carotid intima-media region in b-mode ultrasound images. Image and Vision Computing 28(4), 614–625 (2010)
Santhiyakumari, N., Madheswaran, M.: Non-invasive evaluation of carotid artery wall thickness using improved dynamic programming technique. Signal, Image and Video Processing 2, 183–193 (2008)
Theodoridis, S., Koutroumbas, K.: Pattern Recognition. Academic Press, London (2003)
Gustavsson, T., Liang, Q., Wendelhag, I., Wikstrand, J.: A dynamic programming procedure for automated ultrasonic measurement of the carotid artery. In: Computers in Cardiology, pp. 297–300 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Menchón-Lara, RM., Bastida-Jumilla, MC., Morales-Sánchez, J., Verdú-Monedero, R., Larrey-Ruiz, J., Sancho-Gómez, J.L. (2011). Segmentation of the Carotid Artery in Ultrasound Images Using Neural Networks. In: Ferrández, J.M., Álvarez Sánchez, J.R., de la Paz, F., Toledo, F.J. (eds) New Challenges on Bioinspired Applications. IWINAC 2011. Lecture Notes in Computer Science, vol 6687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21326-7_50
Download citation
DOI: https://doi.org/10.1007/978-3-642-21326-7_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21325-0
Online ISBN: 978-3-642-21326-7
eBook Packages: Computer ScienceComputer Science (R0)