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Multi-contrast MRI Registration of Carotid Arteries Based On Cross-sectional Images and Lumen Boundaries

机译:基于断层图像和管腔边界的颈动脉多对比度MRI配准

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Ischemic stroke has great correlation with carotid atherosclerosis and is mostly caused by vulnerable plaques. It's particularly important to analysis the components of plaques for the detection of vulnerable plaques. Recently plaque analysis based on multi-contrast magnetic resonance imaging has attracted great attention. Though multi-contrast MR imaging has potentials in enhanced demonstration of carotid wall, its performance is hampered by the misalignment of different imaging sequences. In this study, a coarse-to-fine registration strategy based on cross-sectional images and wall boundaries is proposed to solve the problem. It includes two steps: a rigid step using the iterative closest points to register the centerlines of carotid artery extracted from multi-contrast MR images, and a non-rigid step using the thin plate spline to register the lumen boundaries of carotid artery. In the rigid step, the centerline was extracted by tracking the cross-sectional images along the vessel direction calculated by Hessian matrix. In the non-rigid step, a shape context descriptor is introduced to find corresponding points of two similar boundaries. In addition, the deterministic annealing technique is used to find a globally optimized solution. The proposed strategy was evaluated by newly developed three-dimensional, fast and high resolution multi-contrast black blood MR imaging. Quantitative validation indicated that after registration, the overlap of two boundaries from different sequences is 95%, and their mean surface distance is 0.12 mm. In conclusion, the proposed algorithm has improved the accuracy of registration effectively for further component analysis of carotid plaques.
机译:缺血性中风与颈动脉粥样硬化有很大关系,并且主要由易损斑块引起。分析斑块的成分对于检测易损斑块特别重要。最近,基于多对比度磁共振成像的斑块分析引起了极大的关注。尽管多对比度MR成像具有增强颈动脉壁显示的潜力,但其性能因不同成像序列的未对准而受到阻碍。在这项研究中,提出了一种基于横截面图像和壁边界的从粗到细配准策略来解决该问题。它包括两个步骤:使用迭代最近点来记录从多对比度MR图像中提取的颈动脉中心线的刚性步骤,以及使用薄板样条来记录颈动脉管腔边界的非刚性步骤。在刚性步骤中,通过跟踪沿Hessian矩阵计算的血管方向的横截面图像来提取中心线。在非刚性步骤中,引入形状上下文描述符以找到两个相似边界的对应点。另外,确定性退火技术用于找到全局优化的解决方案。通过新开发的三维,快速和高分辨率多对比度黑血MR成像评估了提出的策略。定量验证表明,配准后,来自不同序列的两个边界的重叠率为95%,它们的平均表面距离为0.12 mm。总之,提出的算法有效地提高了配准的准确性,用于进一步分析颈动脉斑块。

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