DocumentCode :
3005576
Title :
Discrete tracking of parametrized curves
Author :
Heibel, Tim Hauke ; Glocker, Ben ; Groher, Martin ; Paragios, Nikos ; Komodakis, Nikos ; Navab, Nassir
Author_Institution :
Comput. Aided Med. Procedures (CAMP), Tech. Univ. Munchen, Munich, Germany
fYear :
2009
fDate :
20-25 June 2009
Firstpage :
1754
Lastpage :
1761
Abstract :
A novel scheme for deformable tracking of curvilinear structures in image sequences is presented. The approach is based on B-spline snakes defined by a set of control points whose optimal configuration is determined through efficient discrete optimization. Each control point is associated with a discrete random variable in a MAP-MRF formulation where a set of labels captures the deformation space. In such a context, generic terms are encoded within this MRF in the form of pairwise potentials. The use of pairwise potentials along with the B-spline representation offers nearly perfect approximation of the continuous domain. Efficient linear programming is considered to recover the approximate optimal solution. The method is successfully applied to the tracking of guide-wires in fluoroscopic X-ray sequences of several hundred frames which requires extremely robust techniques.
Keywords :
Markov processes; approximation theory; image coding; image sequences; linear programming; maximum likelihood estimation; random processes; set theory; splines (mathematics); B-spline representation; MAP-MRF; approximate optimal solution; curvilinear structure; discrete optimization; discrete random variable; discrete tracking; image coding; image sequence; label set; linear programming; maximum a posteriori-Markov random field; parametrized curve; Application software; Biomedical imaging; Computer science; Displacement control; Image sequences; Linear programming; Optimal control; Random variables; Robustness; Spline;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on
Conference_Location :
Miami, FL
ISSN :
1063-6919
Print_ISBN :
978-1-4244-3992-8
Type :
conf
DOI :
10.1109/CVPR.2009.5206714
Filename :
5206714
Link To Document :
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