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.
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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
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DOI: https://doi.org/10.1007/11408031_45
Publisher Name: Springer, Berlin, Heidelberg
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