Optical Flow Estimation in Ultrasound Images Using a Sparse Representation . Ouzir, N. L., Basarab, A., & Tourneret, J. In IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2017), Curaçao, 10/12/2017-13/12/2017, pages 1–5, http://www.ieee.org/, décembre, 2017. IEEE : Institute of Electrical and Electronics Engineers. (Special session)![Optical Flow Estimation in Ultrasound Images Using a Sparse Representation [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex 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.
@InProceedings{ Ou2017.4,
author = {Ouzir, Nora Leïla and Basarab, Adrian and Tourneret, Jean-Yves},
title = "{Optical Flow Estimation in Ultrasound Images Using a Sparse Representation }",
booktitle = "{IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2017), Curaçao, 10/12/2017-13/12/2017}",
year = {2017},
month = {décembre},
publisher = {IEEE : Institute of Electrical and Electronics Engineers},
address = {http://www.ieee.org/},
pages = {1--5},
language = {anglais},
URL = {https://doi.org/10.1109/CAMSAP.2017.8313079 - https://oatao.univ-toulouse.fr/24695/},
note = { (Special session)},
abstract = {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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