Paper Info
Title
Feature-aligned 4D spatiotemporal image registration
Abstract
In this paper, we develop a feature-aware 4D spatiotemporal image registration method. Our model is based on a 4D (3D+time) free-form B-spline deformation model which has both spatial and temporal smoothness. We first introduce an automatic 3D feature extraction and matching method based on an improved 3D SIFT descriptor, which is scale- and rotation- invariant. Then we use the results of feature correspondence to guide an intensity-based deformable image registration. Experimental results show that our method can lead to smooth temporal registration with good matching accuracy; therefore this registration model is potentially suitable for dynamic tumor tracking.
Year
Venue
Keywords
2012
ICPR
computerised tomography,feature-aligned 4d spatiotemporal image registration,matching accuracy,image matching,smoothing methods,automatic 3d feature matching method,spatiotemporal phenomena,3d-plus-time free-form b-spline deformation model,automatic 3d feature extraction method,scale-invariant 3d sift descriptor,cancer,feature extraction,4d free-form b-spline deformation model,object tracking,feature-aware 4d spatiotemporal image registration method,dynamic tumor tracking,tumours,transforms,intensity-based deformable image registration,image registration,spatial smoothness,splines (mathematics),rotation-invariant 3d sift descriptor,temporal smoothness,medical image processing
Field
DocType
ISSN
Template matching,Computer vision,Scale-invariant feature transform,Pattern recognition,Feature detection (computer vision),Feature (computer vision),Computer science,Feature extraction,Video tracking,Artificial intelligence,Kanade–Lucas–Tomasi feature tracker,Image registration
Conference
1051-4651
ISBN
Citations 
PageRank 
978-1-4673-2216-4
4
0.38
References 
Authors
5
6
Name
Order
Citations
PageRank
Huanhuan Xu1482.93
Peizhi Chen240.38
Wuyi Yu3574.94
Amit Sawant4254.81
S. S. Iyengar515225.22
Xin Li66510.73