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Distance transformations in digital images
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Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Extended free-form deformation: a sculpturing tool for 3D geometric modeling
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
A Method for Registration of 3-D Shapes
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ACM Computing Surveys (CSUR)
Curve and surface fitting with splines
Curve and surface fitting with splines
Free-form deformations with lattices of arbitrary topology
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
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Quarterly of Applied Mathematics - Special issue on current and future challenges in the applications of mathematics
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical B-spline refinement
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Curves and surfaces for CAGD: a practical guide
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Scattered Data Interpolation with Multilevel B-Splines
IEEE Transactions on Visualization and Computer Graphics
Alignment by maximization of mutual information
Alignment by maximization of mutual information
Machine Vision: Theory, Algorithms, Practicalities
Machine Vision: Theory, Algorithms, Practicalities
Directly manipulated free-form deformation image registration
IEEE Transactions on Image Processing
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Capturing anatomical shape variability using b-spline registration
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
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ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
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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).