Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Combining the Advantages of Local and Global Optic Flow Methods
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
Structure-Texture Image Decomposition--Modeling, Algorithms, and Parameter Selection
International Journal of Computer Vision
IEEE Transactions on Information Technology in Biomedicine
A Database and Evaluation Methodology for Optical Flow
International Journal of Computer Vision
Myocardial motion analysis from B-mode echocardiograms
IEEE Transactions on Image Processing
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The purpose of this study was to suggest a novel optical flow method to estimate the motion patterns of contrast agents from an ultrasound image. We first recomposed the original image with relative structural and textural parts. We embedded an anisotropic diffusion model into a slightly non-convex total variation-L1 approximation scheme to provide more reliable estimates. An intermediate bilateral filter was adopted after each computation step to prevent over-smoothing effects. Ultrasound data were acquired during continuous injection of contrast agent into a tissue mimicking phantom. The results showed that our method provided robust performance for estimating contrast agent flow patterns.