| Summary: | 碩士 === 國立交通大學 === 資訊科學與工程研究所 === 101 === Abstract
A fast symmetric and diffeomorphic non-rigid registration algorithm for magnetic resonance images (MRIs) is proposed in this work. A log-Euclidean framework is used to model diffeomorphisms, in which the Lie Algebra of the diffeomorphism is modeled by time-invariant velocity fields. The velocity fields are modeled using linear combinations of compactly-supported Wendland radial basis functions. A symmetric correlation ratio combined with a weighted Laplacian model is used as the objective function for optimization. We used a greedy local optimization scheme to increase the speed of the algorithm. In this setup, a symmetric downhill simplex method is used to estimate the coefficient of each radial basis function separately and consecutively. To incorporate the result of initial affine registration while maintaining overall symmetry, a framework utilizing the concept of “halfway space” is devised. This framework can ensure overall symmetry if the affine registration algorithm is symmetric. To increase the speed and accuracy, we used a hierarchical framework in which the RBFs are deployed and estimated in a coarse-to-fine manner. The proposed algorithm was evaluated using the results of 1560 pairwise registrations of 40 T1-weighted MRIs in LPBA40 dataset. According to the evaluation results, the proposed algorithm is completely diffeomorphic and has sub-voxel accuracy in terms of symmetry. The accuracy of the proposed algorithm was evaluated and compared with 14 registration methods using the evaluation framework by Klein et al., 2010. The median target overlap of the proposed algorithm using LPBA40 dataset is higher than all 14 registration methods. In addition, the proposed algorithm is faster than all diffeomorphic registration methods in the comparison when using 5 scale levels.
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