A Novel Nonrigid Registration Algorithm and Applications

J. Rexilius, S. K. Warfield, C. Guttmann, X. Wei, R. Benson, L. Wolfson, M. Shenton, H. Handels, R. Kikinis


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 154 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.

Original languageEnglish
Title of host publicationMICCAI 2001: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001
Number of pages9
PublisherSpringer Verlag
Publication date01.01.2001
ISBN (Print)978-3-540-42697-4
ISBN (Electronic)978-3-540-45468-7
Publication statusPublished - 01.01.2001
Event4th International Conference on Medical Image Computing and Computer-Assisted Intervention
- Utrecht, Netherlands
Duration: 14.10.200117.10.2001
Conference number: 130079


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