Imperial College London

ProfessorDanielRueckert

Faculty of EngineeringDepartment of Computing

Head of Department of Computing
 
 
 
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Contact

 

+44 (0)20 7594 8333d.rueckert Website

 
 
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Location

 

568Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Wang:2012:10.1007/978-3-642-28326-0_5,
author = {Wang, H and Shi, W and Zhuang, X and Duckett, S and Tung, K and Edwards, P and Razavi, R and Ourselin, S and Rueckert, D},
doi = {10.1007/978-3-642-28326-0_5},
pages = {45--54},
title = {Automatic cardiac motion tracking using both untagged and 3D tagged MR images},
url = {http://dx.doi.org/10.1007/978-3-642-28326-0_5},
year = {2012}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - We present a fully automatic framework for cardiac motion tracking based on non-rigid image registration for the analysis of myocardial motion using both untagged and 3D tagged MR images. We detect and track anatomical landmarks in the heart and combine this with intensity-based motion tracking to allow accurately model cardiac motion while significantly reduce the computational complexity. A collaborative similarity measure simultaneously computed in three LA views is employed to register a sequence of images taken during the cardiac cycle to a reference image taken at end-diastole. We then integrate a valve plane tracker into the framework which uses short-axis and long-axis untagged MR images as well as 3D tagged images to estimate a fully four-dimensional motion field of the left ventricle. © 2012 Springer-Verlag.
AU - Wang,H
AU - Shi,W
AU - Zhuang,X
AU - Duckett,S
AU - Tung,K
AU - Edwards,P
AU - Razavi,R
AU - Ourselin,S
AU - Rueckert,D
DO - 10.1007/978-3-642-28326-0_5
EP - 54
PY - 2012///
SN - 0302-9743
SP - 45
TI - Automatic cardiac motion tracking using both untagged and 3D tagged MR images
UR - http://dx.doi.org/10.1007/978-3-642-28326-0_5
ER -