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Proceedings Paper

A symmetric block-matching framework for global registration
Author(s): Marc Modat; David M. Cash; Pankaj Daga; Gawin P. Winston; John S. Duncan; Sébastien Ourselin
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Paper 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.

Paper Details

Date Published: 21 March 2014
PDF: 7 pages
Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90341D (21 March 2014); doi: 10.1117/12.2043652
Show Author Affiliations
Marc Modat, Univ. College London (United Kingdom)
David M. Cash, Univ. College London (United Kingdom)
Pankaj Daga, Univ. College London (United Kingdom)
Gawin P. Winston, Univ. College London (United Kingdom)
John S. Duncan, Univ. College London (United Kingdom)
Sébastien Ourselin, Univ. College London (United Kingdom)

Published in SPIE Proceedings Vol. 9034:
Medical Imaging 2014: Image Processing
Sebastien Ourselin; Martin A. Styner, Editor(s)

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