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Registration of CT Segmented Surfaces and 3-D Cardiac Electroanatomical Maps

机译:CT分割表面和3-D心脏电解剖图的配准

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摘要

To improve the intra-operative image fusion performance in the ablation procedure of atrial fibrillation (AF) treatment, this paper presents a novel registration method for CT segmented surfaces and three-dimensional (3-D) cardiac electroanatomical maps. Random perturbation is introduced to deform the electroanatomical maps in the registration process. The magnitude of deformation automatically attenuates during iterations. Compared to the typical iterative closest point (ICP) algorithm that often converges to local minima, the proposed algorithm is much less sensitive to the initial transformation and able to move out of the local minima and converge to a solution with smaller registration error. Through experiments using both in vivo and simulation data, the results show significant improvements on the registration accuracy and success rate over the existing method being used in the clinical environment. The improved intra-operative registration results can help physicians easily navigate the catheter during the AF interventional procedures.
机译:为了提高房颤(AF)消融过程中的术中图像融合性能,本文提出了一种CT分割表面和三维(3-D)心脏电解剖图的配准方法。引入随机扰动以使配准过程中的电解剖图变形。变形的大小会在迭代过程中自动衰减。与通常会收敛到局部最小值的典型迭代最近点(ICP)算法相比,该算法对初始变换的敏感度要低得多,并且能够移出局部最小值并收敛到具有较小配准误差的解决方案。通过使用体内和模拟数据的实验,结果表明,与临床环境中使用的现有方法相比,配准准确性和成功率有了显着提高。改进的术中配准结果可以帮助医生在AF介入手术过程中轻松导航导管。

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