Ali Rheeda L, Cantwell Chris D, Qureshi Norman A, Roney Caroline H, Lim Phang Boon, Sherwin Spencer J, Siggers Jennifer H, Peters Nicholas S
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:1989-92. doi: 10.1109/EMBC.2015.7318775.
Registration of electroanatomic surfaces and segmented images for the co-localisation of structural and functional data typically requires the manual selection of fiducial points, which are used to initialise automated surface registration. The identification of equivalent points on geometric features by the human eye is heavily subjective, and error in their selection may lead to distortion of the transformed surface and subsequently limit the accuracy of data co-localisation. We propose that the manual trimming of the pulmonary veins through the region of greatest geometrical curvature, coupled with an automated angle-based fiducial-point selection algorithm, significantly reduces target registration error compared with direct manual selection of fiducial points.
为了实现结构和功能数据的共定位，对电解剖表面和分割图像进行配准通常需要手动选择基准点，这些基准点用于初始化自动表面配准。通过肉眼识别几何特征上的等效点具有很大的主观性，其选择误差可能会导致变换后的表面失真，进而限制数据共定位的准确性。我们提出，通过最大几何曲率区域对肺静脉进行手动修剪，再结合基于角度的自动基准点选择算法，与直接手动选择基准点相比，可显著降低目标配准误差。
