Abstract
Doppler has been used for many years for cardiovascular exploration in order to visualize vessel walls as well as anatomical or functional diseases. The use of ultrasound contrast agents makes it possible to improve ultrasonic information.
Recently, nonlinear imaging has emerged as a powerful tool for characterizing pathologies by studying their perfusion. In this paper, we present a new method for estimating the perfusion parameter over a sliding window in order to accurately characterize liver lesions from two-dimensional nonlinear ultrasound images. This method is inspired by the Lucas and Kanade Algorithm coupled with coherence enhancing diffusion in order to suppress the speckle and transparent motions due to the presence of contrast agents.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abd-Elmoniem, K., Kadah, Y.M., et al.: Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion. IEEE Transactions on Biomedical Engineering 49(9), 997–1014 (2002)
Ferrant, M.: Physics-based Deformable Modeling of Volumes and Sur-faces for Medical Image Registration, Segmentation and Visualization. PhD thesis, Universite Catholique de Louvain (2001)
Goldberg, B., Forsberg, F., Raichlen, J.S.: Ultrasound Contrast agents: Basic Principles and Clinical Applications. Dunitz Martin Ltd. (2001)
Goodman, J.W.: Introduction to fourier optics (1968)
Hamarneh, G., Althoff, K., Gustavsson, T.: Snake deformations based on optical flow forces for contrast agent tracking in echocardiography. In: Proceedings of the Swedish symposium on Image Analysis, SSAB (2000)
Haussecker, H.W., Fleet, D.J.: Computing optical flow with physical models of brightness variation. IEEE Trans. Pattern Analysis Machine Intelligence 23(6), 661–673 (2001)
Hemmendorff, M.: Motion estimation and compensation in medical imaging. Master’s thesis, Linköping University, SE-581 83 Linköping, Sweden, LiTH-ISY-EX-1750 (2001)
Kissi, A., Cormier, S., Pourcelot, L., Bleuzen, A., Tranquart, T.: Contrast enhanced ultrasound image segmentation based on fuzzy competitive clustering and anisotropic diffusion. In: Proceedings of the 2004 IEEE EMBS, pp. 587–592 (2004)
Malpica, N., Desco, M., et al.: Tracking of regions-of-interest in myocardial contrast echocardiography. Ultrasound in Medicine and Biology 30(30), 303–309 (2004)
Spies, H., Scharr, H.: Accurate optical flow in noisy image sequences. In: Proceedings of the 2001 ICCV, pp. 587–592 (2001)
Tranquart, F., Bleuzen, A., et al.: Echographie de contraste et affections hépatiques (contrast ultrasound imaging in liver disease). J. Radiol 84, 2025–2040 (2003)
Tranquart, F., Grenier, N.: Imagerie ultrasonore non linéaire (nonlinear ultrasound imaging). J. Radiol 81, 1731–1735 (2000)
Weickert, J., Brox, T.: Nonlinear matrix diffusion for optical flow estimation. In: Van Gool, L. (ed.) DAGM 2002. LNCS, vol. 2449, pp. 446–453. Springer, Heidelberg (2002)
Weickert, J.: Coherence-enhancing diffusion filtering. Internal Journal of Computer Vision 31(3), 111–127 (1999)
Weickert, J., Scharr, H.: A scheme for coherence-enhancing diffusion filtering with optimized rotation invariance. Computing Supplement 11, 221–236 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kissi, A., Cormier, S., Pourcelot, L., Bleuzen, A., Tranquart, F. (2005). Perfusion Analysis of Nonlinear Liver Ultrasound Images Based on Nonlinear Matrix Diffusion. In: Kimmel, R., Sochen, N.A., Weickert, J. (eds) Scale Space and PDE Methods in Computer Vision. Scale-Space 2005. Lecture Notes in Computer Science, vol 3459. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11408031_45
Download citation
DOI: https://doi.org/10.1007/11408031_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25547-5
Online ISBN: 978-3-540-32012-8
eBook Packages: Computer ScienceComputer Science (R0)