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Updated: May 2, 2026

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
Published on: February 12, 2011
Whole myocardium tracking in 2D-echocardiography in multiple orientations using a motion constrained level-set
T Dietenbeck1, D Barbosa2, M Alessandrini1
1Université de Lyon, CREATIS, CNRS UMR5220, INSERM U1044, Université Lyon 1, INSA-LYON, France.
Insights
This study enhances myocardium segmentation in echocardiographic images using a novel level-set method with temporal coherence. The improved technique accurately tracks heart muscle motion, aiding in heart disease diagnosis.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Cardiovascular Imaging
Background:
- Echocardiographic image segmentation and tracking of the myocardium are crucial for diagnosing heart disease.
- Echographic images present challenges like low contrast, speckle noise, signal dropout, and shadows, complicating accurate analysis.
Purpose of the Study:
- To extend an existing level-set method for robust myocardium tracking in echocardiographic sequences.
- To improve temporal coherence and accuracy in cardiac image analysis.
Main Methods:
- An extended level-set method incorporating a novel motion prior energy term for temporal coherence.
- Spatially adaptive adjustment of hyperparameters using prior knowledge of echocardiographic regions.
- Evaluation against expert segmentations and a state-of-the-art method on a dataset of 15 sequences (approximately 900 images) across three views.
Main Results:
- The proposed method demonstrates results consistent with inter-observer variability.
- Outperforms a current state-of-the-art method in accuracy and robustness.
- Exhibits stability across various parameter settings, confirmed by a comprehensive parameter influence study.
Conclusions:
- The enhanced level-set method provides accurate and robust myocardium segmentation and tracking in echocardiographic sequences.
- The approach effectively addresses challenges in cardiac imaging, offering a valuable tool for heart disease diagnosis.
Abstract:
The segmentation and tracking of the myocardium in echocardiographic sequences is an important task for the diagnosis of heart disease. This task is difficult due to the inherent problems of echographic images (i.e. low contrast, speckle noise, signal dropout, presence of shadows). In this article, we extend a level-set method recently proposed in Dietenbeck et al. (2012) in order to track the whole myocardium in echocardiographic sequences. To this end, we enforce temporal coherence by adding a new motion prior energy to the existing framework. This motion prior term is expressed as new constraint that enforces the conservation of the levels of the implicit function along the image sequence. Moreover, the robustness of the proposed method is improved by adjusting the associated hyperparameters in a spatially adaptive way, using the available strong a priori about the echocardiographic regions to be segmented. The accuracy and robustness of the proposed method is evaluated by comparing the obtained segmentation with experts references and to another state-of-the-art method on a dataset of 15 sequences (≃ 900 images) acquired in three echocardiographic views. We show that the algorithm provides results that are consistent with the inter-observer variability and outperforms the state-of-the-art method. We also carry out a complete study on the influence of the parameters settings. The obtained results demonstrate the stability of our method according to those values.
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