Image registration using hierarchical B-splines

Zhiyong Xie; Gerald E. Farin

doi:10.1109/TVCG.2004.1260760

Image registration using hierarchical B-splines

Zhiyong Xie, Gerald E. Farin

Computing and Augmented Intelligence, School of (IAFSE-SCAI)

Research output: Contribution to journal › Article › peer-review

112 Scopus citations

Abstract

Hierarchical B-splines have been widely used for shape modeling since their discovery by Forsey and Bartels. In this paper, we present an application of this concept, in the form of free-form deformation, to image registration by matching two images at increasing levels of detail. Results using MRI brain data are presented that demonstrate high degrees of matching while unnecessary distortions are avoided. We compare our results with the nonlinear ICP (Iterative Closest Point) algorithm (used for landmark-based registration) and optical flow (used for intensity-based registration).

Original language	English (US)
Pages (from-to)	85-94
Number of pages	10
Journal	IEEE Transactions on Visualization and Computer Graphics
Volume	10
Issue number	1
DOIs	https://doi.org/10.1109/TVCG.2004.1260760
State	Published - Jan 2004

Keywords

Free form deformation
Hierarchical B-splines
Image registration
Iterative closest point
Optical flow
Scattered data approximation

ASJC Scopus subject areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Computer Graphics and Computer-Aided Design

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10.1109/TVCG.2004.1260760

Cite this

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title = "Image registration using hierarchical B-splines",

abstract = "Hierarchical B-splines have been widely used for shape modeling since their discovery by Forsey and Bartels. In this paper, we present an application of this concept, in the form of free-form deformation, to image registration by matching two images at increasing levels of detail. Results using MRI brain data are presented that demonstrate high degrees of matching while unnecessary distortions are avoided. We compare our results with the nonlinear ICP (Iterative Closest Point) algorithm (used for landmark-based registration) and optical flow (used for intensity-based registration).",

keywords = "Free form deformation, Hierarchical B-splines, Image registration, Iterative closest point, Optical flow, Scattered data approximation",

author = "Zhiyong Xie and Farin, {Gerald E.}",

note = "Funding Information: This work was funded in part by the Arizona Alzheimer{\textquoteright}s Disease Research Center and Grant MH57899 from the US National Institute of Mental Health and the US National Institute on Aging and by a US National Science Foundation KDI grant to Arizona State University. The authors would like to thank Dr. Eric Reiman and Dr. K.W. Chen of Good Samaritan PET center for all their help with this research.",

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N2 - Hierarchical B-splines have been widely used for shape modeling since their discovery by Forsey and Bartels. In this paper, we present an application of this concept, in the form of free-form deformation, to image registration by matching two images at increasing levels of detail. Results using MRI brain data are presented that demonstrate high degrees of matching while unnecessary distortions are avoided. We compare our results with the nonlinear ICP (Iterative Closest Point) algorithm (used for landmark-based registration) and optical flow (used for intensity-based registration).

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Image registration using hierarchical B-splines

Abstract

Keywords

ASJC Scopus subject areas

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