ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
LV Motion and Strain Computation from tMRI Based on Meshless Deformable Models
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Large Diffeomorphic FFD Registration for Motion and Strain Quantification from 3D-US Sequences
FIMH '09 Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart
A Dynamical Shape Prior for LV Segmentation from RT3D Echocardiography
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Quantitative validation of optical flow based myocardial strain measures using sonomicrometry
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Automatic active appearance model segmentation of 3D echocardiograms
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
Cardiac motion estimation from 3D echocardiography with spatiotemporal regularization
FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
STACOM'11 Proceedings of the Second international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
Quadrature filter based motion analysis for 3d ultrasound sequences
STACOM'12 Proceedings of the third international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
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Global and regional cardiac deformation provides important information on myocardial (dys-)function in a variety of clinical settings. Recent developments in the field of echocardiography have allowed the cardiologist to quantify cardiac deformation in a non-invasive manner. Unstitched volumetric data can be captured in a high frame rate by real-time ultrasound imaging. However, most existing methods for measuring myocardial mechanics are often limited to measurements in one or two dimensions. Since myocardial tissue is virtually incompressible, the ventricular wall contains the same volume during the cardiac cycle and, thus, deforms in three dimensions. In this paper, we propose an automatic method to estimate the regional 3D myocardial mechanics on ultrasound images by recovering the 3D non-rigid deformation of the myocardium. The key advantage of our method is fusing multiple information, such as speckle patterns, image gradients, boundary detection, and motion prediction, to achieve a robust tracking on 3D+t ultrasound data. Preliminary results in both in-vitro and in-vivo experiments confirmed these findings in a quantitative manner, as the motion and mechanical parameters, such as displacement and strain, estimated by our method are close to both the ground-truth data and the clinical evaluation. The proposed method is efficient and achieves high speed performance of less than 1 second per frame for volumetric ultrasound data.