Abstract
Motion estimation from cardiac image is a very important technique to study the architecture and function of heart. However quantitative motion analysis from cardiac images is still a challenging problem due to the complexity of cardiac motion and limitations in spatial and temporal image resolutions. We develop a robust temporally consistent diffeomorphic motion estimation algorithm based on mutual information similarity measurement. It extends the current large deformation diffeomorphic registration method by the usage of statistical similarity measurement. In our algorithm, the spatial transformation is parameterized by a smooth velocity field with a transport equation. The optimal velocity field is obtained by minimizing a geodesic path on the diffeomorphic transformation manifold and simultaneously minimizing the frame to frame negative mutual information. The Euler-Lagrange equation of the variational functional is derived and the numerical method based on 3D+t B-spline is proposed. Our method is applied to the simulated and real 3D+t echocardiographic sequences. Experimental results show the improvements of our method over the diffeomorphic method using the sum of squared difference similarity metric.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops |
| Pages | 84-90 |
| Number of pages | 7 |
| DOIs | |
| State | Published - 2012 |
| Event | 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2012 - Providence, RI, United States Duration: Jun 16 2012 → Jun 21 2012 |
Other
| Other | 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2012 |
|---|---|
| Country | United States |
| City | Providence, RI |
| Period | 6/16/12 → 6/21/12 |
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ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
Cite this
Temporally consistent diffeomorphic motion estimation with mutual information : Application to echocardiographic sequences. / Zhang, Zhijun; Sahn, David; Song, Xubo.
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2012. p. 84-90 6239252.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Temporally consistent diffeomorphic motion estimation with mutual information
T2 - Application to echocardiographic sequences
AU - Zhang, Zhijun
AU - Sahn, David
AU - Song, Xubo
PY - 2012
Y1 - 2012
N2 - Motion estimation from cardiac image is a very important technique to study the architecture and function of heart. However quantitative motion analysis from cardiac images is still a challenging problem due to the complexity of cardiac motion and limitations in spatial and temporal image resolutions. We develop a robust temporally consistent diffeomorphic motion estimation algorithm based on mutual information similarity measurement. It extends the current large deformation diffeomorphic registration method by the usage of statistical similarity measurement. In our algorithm, the spatial transformation is parameterized by a smooth velocity field with a transport equation. The optimal velocity field is obtained by minimizing a geodesic path on the diffeomorphic transformation manifold and simultaneously minimizing the frame to frame negative mutual information. The Euler-Lagrange equation of the variational functional is derived and the numerical method based on 3D+t B-spline is proposed. Our method is applied to the simulated and real 3D+t echocardiographic sequences. Experimental results show the improvements of our method over the diffeomorphic method using the sum of squared difference similarity metric.
AB - Motion estimation from cardiac image is a very important technique to study the architecture and function of heart. However quantitative motion analysis from cardiac images is still a challenging problem due to the complexity of cardiac motion and limitations in spatial and temporal image resolutions. We develop a robust temporally consistent diffeomorphic motion estimation algorithm based on mutual information similarity measurement. It extends the current large deformation diffeomorphic registration method by the usage of statistical similarity measurement. In our algorithm, the spatial transformation is parameterized by a smooth velocity field with a transport equation. The optimal velocity field is obtained by minimizing a geodesic path on the diffeomorphic transformation manifold and simultaneously minimizing the frame to frame negative mutual information. The Euler-Lagrange equation of the variational functional is derived and the numerical method based on 3D+t B-spline is proposed. Our method is applied to the simulated and real 3D+t echocardiographic sequences. Experimental results show the improvements of our method over the diffeomorphic method using the sum of squared difference similarity metric.
UR - http://www.scopus.com/inward/record.url?scp=84865003008&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84865003008&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2012.6239252
DO - 10.1109/CVPRW.2012.6239252
M3 - Conference contribution
AN - SCOPUS:84865003008
SN - 9781467316118
SP - 84
EP - 90
BT - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ER -