Title :
Feature-aligned 4D spatiotemporal image registration
Author :
Huanhuan Xu ; Peizhi Chen ; Wuyi Yu ; Sawant, Ashwini ; Iyengar, S.S. ; Xin Li
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.
Keywords :
cancer; computerised tomography; feature extraction; image matching; image registration; medical image processing; object tracking; smoothing methods; spatiotemporal phenomena; splines (mathematics); transforms; tumours; 3D-plus-time free-form B-spline deformation model; 4D free-form B-spline deformation model; automatic 3D feature extraction method; automatic 3D feature matching method; dynamic tumor tracking; feature-aligned 4D spatiotemporal image registration; feature-aware 4D spatiotemporal image registration method; intensity-based deformable image registration; matching accuracy; rotation-invariant 3D SIFT descriptor; scale-invariant 3D SIFT descriptor; spatial smoothness; temporal smoothness; Feature extraction; Histograms; Image registration; Lungs; Spatiotemporal phenomena; Splines (mathematics); Tumors;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4