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Signal, Image and Video Processing

, Volume 11, Issue 3, pp 455–462 | Cite as

A parametric intensity-based 3D image registration method for magnetic resonance imaging

  • Huajun Song
  • Peihua QiuEmail author
Original Paper

Abstract

Image registration (IR) aims to map one image to another of a same scene. With rapid progress in image acquisition technologies, 3D IR becomes an important problem in magnetic resonance imaging (MRI) and other applications. In the literature, however, most IR methods are for 2D images and there are only a limited number of 3D methods available. Because 3D images have much complicated structure than their 2D counterparts, 3D IR is not just a simple generalization of the 2D IR problem. In this paper, we develop a 3D IR method that can handle cases with affine geometric transformations well. By its definition, an affine transformation maps a line to a line, and it includes rotation, translation, and scaling as special cases. In practice, most geometric transformations involved in IR problems are affine transformations. Therefore, our proposed method can find many IR applications. It is shown that this method works well in various cases, including cases when the data size of a 3D image is reduced for different reasons. This latter property makes it attractive for many 3D IR applications, since 3D images are often big in data size and it is natural to reduce their size for fast computation.

Keywords

Function approximation Geometric transformation Image mapping Iterative algorithm Kernel estimation Performance evaluation 

Notes

Acknowledgments

The authors acknowledge the grant support from the National Natural Science Foundation of China (No.61305012) and from US National Science Foundation (DMS1405698). We also thank the editor, the associate editor and three referees for their constructive comments and suggestions, which greatly improved the quality of the paper.

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Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  1. 1.College of Information and Control EngineeringChina University of Petroleum (East China)QingdaoChina
  2. 2.Department of BiostatisticsUniversity of FloridaGainesvilleUSA

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