@inproceedings{ae9065d821684a7dae7641325031cff6,
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.",
author = "Huanhuan Xu and Peizhi Chen and Wuyi Yu and Amit Sawant and Iyengar, {S. S.} and Xin Li",
year = "2012",
language = "English (US)",
isbn = "9784990644109",
series = "Proceedings - International Conference on Pattern Recognition",
pages = "2639--2642",
booktitle = "ICPR 2012 - 21st International Conference on Pattern Recognition",
note = "21st International Conference on Pattern Recognition, ICPR 2012 ; Conference date: 11-11-2012 Through 15-11-2012",
}