A symmetric block-matching framework for global registration

Marc Modat; David M. Cash; Pankaj Daga; Gawin P. Winston; John S. Duncan; Sébastien Ourselin

doi:10.1117/12.2043652

21 March 2014 A symmetric block-matching framework for global registration

Marc Modat, David M. Cash, Pankaj Daga, Gawin P. Winston, John S. Duncan, Sébastien Ourselin

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 90341D (2014) https://doi.org/10.1117/12.2043652
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Most registration algorithms suffer from a directionality bias that has been shown to largely impact on subsequent analyses. Several approaches have been proposed in the literature to address this bias in the context of non-linear registration but little work has been done in the context of global registration. We propose a symmetric approach based on a block-matching technique and least trimmed square regression. The proposed method is suitable for multi-modal registration and is robust to outliers in the input images. The symmetric framework is compared to the original asymmetric block-matching technique, outperforming it in terms accuracy and robustness.

Citation Download Citation

Marc Modat, David M. Cash, Pankaj Daga, Gawin P. Winston, John S. Duncan, and Sébastien Ourselin "A symmetric block-matching framework for global registration", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90341D (21 March 2014); https://doi.org/10.1117/12.2043652

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