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Communication Dans Un Congrès Année : 2018

Optical Flow Estimation in Ultrasound Images Using a Sparse Representation

Résumé

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.
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Dates et versions

hal-03656602 , version 1 (02-05-2022)

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Citer

Nora Leïla Ouzir, Jean-Yves Tourneret, Adrian Basarab. Optical Flow Estimation in Ultrasound Images Using a Sparse Representation. 7th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2017), Dec 2017, Curaçao, Netherlands Antilles. pp.1-5, ⟨10.1109/CAMSAP.2017.8313079⟩. ⟨hal-03656602⟩
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