Fast Diffeomorphic Image Registration via Fourier-Approximated Lie Algebras

被引:31
|
作者
Zhang, Miaomiao [1 ]
Fletcher, P. Thomas [2 ]
机构
[1] Lehigh Univ, 113 Res Dr, Bethlehem, PA 18015 USA
[2] Univ Utah, 72 S Cent Campus Dr, Salt Lake City, UT USA
基金
美国国家科学基金会;
关键词
Fourier-approximated Lie algebras; Geodesic shooting; Diffeomorphic image registration; STATISTICS; FLOWS;
D O I
10.1007/s11263-018-1099-x
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper introduces Fourier-approximated Lie algebras for shooting (FLASH), a fast geodesic shooting algorithm for diffeomorphic image registration. We approximate the infinite-dimensional Lie algebra of smooth vector fields, i.e., the tangent space at the identity of the diffeomorphism group, with a low-dimensional, bandlimited space. We show that most of the computations for geodesic shooting can be carried out entirely in this low-dimensional space. Our algorithm results in dramatic savings in time and memory over traditional large-deformation diffeomorphic metric mapping algorithms, which require dense spatial discretizations of vector fields. To validate the effectiveness of FLASH, we run pairwise image registration on both 2D synthetic data and real 3D brain images and compare with the state-of-the-art geodesic shooting methods. Experimental results show that our algorithm dramatically reduces the computational cost and memory footprint of diffemorphic image registration with little or no loss of accuracy.
引用
收藏
页码:61 / 73
页数:13
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