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19 September 2014 Global image registration using a symmetric block-matching approach
Marc Modat, David M. Cash, Pankaj Daga, Gavin P. Winston, John S. Duncan, Sébastien Ourselin
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Journal of Medical Imaging, Vol. 1, Issue 2, 024003 (September 2014). https://doi.org/10.1117/1.JMI.1.2.024003
Abstract
Most medical image registration algorithms suffer from a directionality bias that has been shown to largely impact subsequent analyses. Several approaches have been proposed in the literature to address this bias in the context of nonlinear registration, but little work has been done for global registration. We propose a symmetric approach based on a block-matching technique and least-trimmed square regression. The proposed method is suitable for multimodal registration and is robust to outliers in the input images. The symmetric framework is compared with the original asymmetric block-matching technique and is shown to outperform it in terms of accuracy and robustness. The methodology presented in this article has been made available to the community as part of the NiftyReg open-source package.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Marc Modat, David M. Cash, Pankaj Daga, Gavin P. Winston, John S. Duncan, and Sébastien Ourselin "Global image registration using a symmetric block-matching approach," Journal of Medical Imaging 1(2), 024003 (19 September 2014). https://doi.org/10.1117/1.JMI.1.2.024003
Published: 19 September 2014
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KEYWORDS
Image registration
Magnetic resonance imaging
Computed tomography
Databases
Positron emission tomography
Brain
Medical imaging
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