Evaluation of optimal control-based deformable registration model
Master Thesis
2014
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University of Cape Town
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Abstract
The deformable image registration is central to many challenges in medical imaging applications. The basic idea of the deformable image registration problem is to find an approximation of a reasonable deformation which transforms one image to match another based on a chosen similarity measure. A reasonable deformation can be thought of as one that is physically realizable. A number of models, guaranteeing reasonable deformations, have been proposed and implemented with success under various similarity measures. One such model is based on the grid deformation method (GDM) and is the method of interest in this thesis. This work focuses on the evaluation of an optimal control-based model for solving the deformable image registration problem which is formulated using GDM. This model is compared with other four well-known variational-based deformable image registration models: elastic, fluid, diffusion and curvature models. Using similarity and deformation quality measures as performance indices, the non-dominated sorting genetic algorithm (NSGA-II) is applied to approximate the Pareto fronts for each model to facilitate proper evaluation. The Pareto fronts are also visualized using level diagrams analysis.
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Includes bibliographical references.
Reference:
Matjelo, N. 2014. Evaluation of optimal control-based deformable registration model. University of Cape Town.