4.5 Article

A coarse-to-fine registration method for three-dimensional MR images

Journal

MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
Volume 59, Issue 2, Pages 457-469

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11517-021-02317-x

Keywords

Image registration; Coarse-to-fine; Feature points extraction; Maximizing mutual information

Funding

  1. New generation information technology innovation project and Universities key scientific research project of Education Department of Henan Province [2018A03003, 21A520042]
  2. Science and technology research project of Henan province [172102210003]
  3. Startup Research Fund of Zhengzhou University [F0001297]

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A coarse-to-fine method is proposed in this study for pairwise 3D MR image rigid registration, aiming to improve registration accuracy through extracting image feature points, calculating grey histograms, and maximizing mutual information. Experimental results show that the proposed method outperforms traditional methods in terms of registration success rate and accuracy.
Three-dimensional (3D) multimodal magnetic resonance (MR) image registration aims to align similar things in different MR images spatially. Such a technology is useful in auxiliary disease diagnosis and surgical treatment. However, inconsistent intensity correspondence and large initial displacement contribute to the difficulty in registering multimodal MR volumes. A coarse-to-fine method is proposed in this study for pairwise 3D MR image rigid registration. Firstly, the proposed method extracts image feature points to form unregistered point sets and performs coarse registration based on point set registration to reduce the initial displacements of offset images effectively. Then, this method calculates a grey histogram based on voxels in the adaptive region of interest and further improves registration accuracy by maximizing mutual information of coarse-registered images. Some representative registration methods are compared on the basis of three MR image datasets to evaluate the performance of the proposed method. Experimental results show that the proposed method improved more in registration success rate and accuracy compared with conventional registration methods, especially when initial displacements are large.

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