Optical Flow Estimation in Ultrasound Images Using a Sparse Representation

This paper introduces a 2D optical flow estimation method for cardiac ultrasound imaging based on a sparse representation. The optical flow problem is regularized using a classical gradient-based smoothness term combined with a sparsity inducing regularization that uses a learned cardiac flow dictionary. A particular emphasis is put on the influence of the spatial and sparse regularizations on the optical flow estimation problem. A comparison with state-of-the-art methods using realistic simulations shows the competitiveness of the proposed method for cardiac motion estimation in ultrasound images.