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Proceedings Paper

A multi-resolution strategy for a multi-objective deformable image registration framework that accommodates large anatomical differences
Author(s): Tanja Alderliesten; Peter A. N. Bosman; Jan-Jakob Sonke; Arjan Bel
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Paper Abstract

Currently, two major challenges dominate the field of deformable image registration. The first challenge is related to the tuning of the developed methods to specific problems (i.e. how to best combine different objectives such as similarity measure and transformation effort). This is one of the reasons why, despite significant progress, clinical implementation of such techniques has proven to be difficult. The second challenge is to account for large anatomical differences (e.g. large deformations, (dis)appearing structures) that occurred between image acquisitions. In this paper, we study a framework based on multi-objective optimization to improve registration robustness and to simplify tuning for specific applications. Within this framework we specifically consider the use of an advanced model-based evolutionary algorithm for optimization and a dual-dynamic transformation model (i.e. two “non-fixed” grids: one for the source- and one for the target image) to accommodate for large anatomical differences. The framework computes and presents multiple outcomes that represent efficient trade-offs between the different objectives (a so-called Pareto front). In image processing it is common practice, for reasons of robustness and accuracy, to use a multi-resolution strategy. This is, however, only well-established for single-objective registration methods. Here we describe how such a strategy can be realized for our multi-objective approach and compare its results with a single-resolution strategy. For this study we selected the case of prone-supine breast MRI registration. Results show that the well-known advantages of a multi-resolution strategy are successfully transferred to our multi-objective approach, resulting in superior (i.e. Pareto-dominating) outcomes.

Paper Details

Date Published: 21 March 2014
PDF: 7 pages
Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90343G (21 March 2014); doi: 10.1117/12.2042856
Show Author Affiliations
Tanja Alderliesten, Academisch Medisch Ctr. (Netherlands)
Peter A. N. Bosman, Ctr. voor Wiskunde en Informatica (Netherlands)
Jan-Jakob Sonke, The Netherlands Cancer Institute (Netherlands)
Arjan Bel, Academisch Medisch Ctr. (Netherlands)

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

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