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Cardiac motion estimation in ultrasound images using spatial and sparse regularizations

Ouzir, Nora Leïla and Basarab, Adrian and Tourneret, Jean-Yves Cardiac motion estimation in ultrasound images using spatial and sparse regularizations. (2018) In: ICIP 2017: IEEE International Conference on Image Processing, 17 September 2017 - 20 September 2017 (Beijing, China).

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Official URL: https://doi.org/10.1109/ICIP.2017.8296387

Abstract

This paper investigates a new method for cardiac motion estimation in 2D ultrasound images. The motion estimation problem is formulated as an energy minimization with spatial and sparse regularizations. In addition to a classical spatial smoothness constraint, the proposed method exploits the sparse properties of the cardiac motion to regularize the solution via an appropriate dictionary learning step. The proposed method is evaluated in terms of motion estimation and strain accuracy and compared with state-of-the-art algorithms using a dataset of realistic simulations. These simulation results show that the proposed method provides very promising results for myocardial motion estimation.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-02863743
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Funders:
CIMI Labex (grant ANR-11-LABX-0040-CIMI)
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Deposited On:10 Jun 2020 13:14

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