Perfusion analysis of nonlinear liver ultrasound images based on nonlinear matrix diffusion

Authors:
A. Kissi;S. Cormier;L. Pourcelot;A. Bleuzen;F. Tranquart
Affiliations:
INSERM unité 619, CHRU Bretonneau, Tours, France;CRESTIC-L.E.R.I., Université de Reims Champagne-Ardenne, Reims Cedex 2 Reims, France;INSERM unité 619, CHRU Bretonneau, Tours, France;INSERM unité 619, CHRU Bretonneau, Tours, France;INSERM unité 619, CHRU Bretonneau, Tours, France
Venue:
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Year:
2005

Citing 3
Cited 0

Computing Optical Flow with Physical Models of Brightness Variation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Coherence-Enhancing Diffusion Filtering

International Journal of Computer Vision
Nonlinear Matrix Diffusion for Optic Flow Estimation

Proceedings of the 24th DAGM Symposium on Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

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.