Literature DB >> 33515131

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

Cuixia Li1, Yuanyuan Zhou1, Yinghao Li2, Shanshan Yang1.   

Abstract

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.

Entities:  

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

Year:  2021        PMID: 33515131     DOI: 10.1007/s11517-021-02317-x

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  2 in total

1.  Intensity-based image registration using robust correlation coefficients.

Authors:  Jeongtae Kim; Jeffrey A Fessler
Journal:  IEEE Trans Med Imaging       Date:  2004-11       Impact factor: 10.048

2.  Multiple-correlation similarity for block-matching based fast CT to ultrasound registration in liver interventions.

Authors:  Jyotirmoy Banerjee; Yuanyuan Sun; Camiel Klink; Renske Gahrmann; Wiro J Niessen; Adriaan Moelker; Theo van Walsum
Journal:  Med Image Anal       Date:  2019-02-07       Impact factor: 8.545

  2 in total

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