Abstract：Recently multi-contrast magnetic resonance imaging (MRI) has become a powerful tool for plaque analyzing due to its strong potential in enhanced demonstration of carotid wall, but its performance is hampered by the misalignment of difference imaging sequences. To achieve accurate vessel registration of multi-sequence images, a two-step coarse-to-fine registration strategy was proposed in this study. First, the iterative closest point was applied to realize the rigid registration of the centerlines of the multi-contrast images, and then the thin plate spline was used to realize the non-rigid registration based on the boundaries of carotid artery. In the second step, to find the corresponding points of the boundaries in different sequences, a shape context descriptor was innovatively introduced to screen the boundary points. In addition, the deterministic annealing technique was employed to find a globally optimized solution. The effectiveness of the proposed algorithm was quantitatively evaluated by novel three-dimensional (3D) multi-contrast vessel wall MRI sequences. The results indicated that after registration, the overlap of two boundaries from different sequences was more than 95%, and their mean surface distance was 0.12 mm, which improved the accuracy of registration effectively and laid the foundation for further component analysis.
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