TY - GEN
T1 - Consistent estimation of cardiac motions by 4D image registration
AU - Shen, Dinggang
AU - Sundar, Hari
AU - Xue, Zhong
AU - Fan, Yong
AU - Litt, Harold
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2005
Y1 - 2005
N2 - A 4D image registration method is proposed for consistent estimation of cardiac motion from MR image sequences. Under this 4D registration framework, all 3D cardiac images taken at different time-points are registered simultaneously, and motion estimated is enforced to be spatiotemporally smooth, thereby overcoming potential limitations of some methods that typically estimate cardiac deformation sequentially from one frame to another, instead of treating the entire set of images as a 4D volume. To facilitate our image matching process, an attribute vector is designed for each point in the image to include intensity, boundary and geometric moment invariants (GMIs). Hierarchical registration of two image sequences is achieved by using the most distinctive points for initial registration of two sequences and gradually adding less-distinctive points for refinement of registration. Experimental results on real data demonstrate good performance of the proposed method in registering cardiac images and estimating motions from cardiac image sequences.
AB - A 4D image registration method is proposed for consistent estimation of cardiac motion from MR image sequences. Under this 4D registration framework, all 3D cardiac images taken at different time-points are registered simultaneously, and motion estimated is enforced to be spatiotemporally smooth, thereby overcoming potential limitations of some methods that typically estimate cardiac deformation sequentially from one frame to another, instead of treating the entire set of images as a 4D volume. To facilitate our image matching process, an attribute vector is designed for each point in the image to include intensity, boundary and geometric moment invariants (GMIs). Hierarchical registration of two image sequences is achieved by using the most distinctive points for initial registration of two sequences and gradually adding less-distinctive points for refinement of registration. Experimental results on real data demonstrate good performance of the proposed method in registering cardiac images and estimating motions from cardiac image sequences.
UR - http://www.scopus.com/inward/record.url?scp=33744780479&partnerID=8YFLogxK
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U2 - 10.1007/11566489_111
DO - 10.1007/11566489_111
M3 - Conference contribution
C2 - 16686046
AN - SCOPUS:33744780479
SN - 3540293264
SN - 9783540293262
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 902
EP - 910
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings
PB - Springer Verlag
T2 - 8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005
Y2 - 26 October 2005 through 29 October 2005
ER -