Imperial College London
Alternate

ProfessorDanielRueckert

Faculty of Engineering, Department of Computing

Professor of Visual Information Processing
 
 
 
//

Contact

 

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

 
 
//

Location

 

568Huxley BuildingSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@inproceedings{Shi:2012:10.1007/978-3-642-33418-4_81,
author = {Shi, W and Zhuang, X and Pizarro, L and Bai, W and Wang, H and Tung, KP and Edwards, P and Rueckert, D},
doi = {10.1007/978-3-642-33418-4_81},
pages = {659--666},
title = {Registration using sparse free-form deformations},
url = {http://dx.doi.org/10.1007/978-3-642-33418-4_81},
year = {2012}
}
Download

RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Non-rigid image registration using free-form deformations (FFD) is a widely used technique in medical image registration. The balance between robustness and accuracy is controlled by the control point grid spacing and the amount of regularization. In this paper, we revisit the classic FFD registration approach and propose a sparse representation for FFDs using the principles of compressed sensing. The sparse free-form deformation model (SFFD) can capture fine local details such as motion discontinuities without sacrificing robustness. We demonstrate the capabilities of the proposed framework to accurately estimate smooth as well as discontinuous deformations in 2D and 3D image sequences. Compared to the classic FFD approach, a significant increase in registration accuracy can be observed in natural images (61%) as well as in cardiac MR images (53%) with discontinuous motions.
AU  - Shi,W
AU  - Zhuang,X
AU  - Pizarro,L
AU  - Bai,W
AU  - Wang,H
AU  - Tung,KP
AU  - Edwards,P
AU  - Rueckert,D
DO  - 10.1007/978-3-642-33418-4_81
EP  - 666
PY  - 2012///
SN  - 0302-9743
SP  - 659
TI  - Registration using sparse free-form deformations
UR  - http://dx.doi.org/10.1007/978-3-642-33418-4_81
ER  -
Download