A novel nonrigid registration algorithm and applications

R. Rexilius, S. K. Warfield, G. G. Guttmann, X. Wei, R. Benson, L. Wolfson, M. E. Shenton, H. Handels, R. Kikinis
Proceedings of the 4th International Conference on Medical Image Computing and Computer Assisted Intervention MICCAI 2001
Pages 923-931
2001

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Abstract

In this paper we describe a new algorithm for nonrigid registration of brain images based on an elastically deformable model. The use of registration methods has become an important tool for computer-assisted diagnosis and surgery. Our goal was to improve analysis in various applications of neurology and neurosurgery by improving nonrigid registration. A local gray level similarity measure is used to make an initial sparse displacement field estimate. The field is initially estimated at locations determined by local features, and then a linear elastic model is used to infer the volumetric deformation across the image. The associated partial differential equation is solved by a finite element approach. A model of empirically observed variability of the brain was created from a dataset of young adults. Both homogeneous and inhomogeneous elasticity models were compared. The algorithm has been applied to medical applications including intraoperative images of neurosurgery showing brain shift and a study of gait and balance disorder. diffusionMRI.html

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Reference

Rexilius R, Warfield SK, Guttmann GG, Wei X, Benson R, Wolfson L, Shenton ME, Handels H, Kikinis R. A novel nonrigid registration algorithm and applications. In Proceedings of the 4th International Conference on Medical Image Computing and Computer Assisted Intervention MICCAI 2001. 2001;923-931.

Grants

NIH P41 RR13218, NIH P01-CA67165, NIH R01 RR11747