We propose an AR navigation method to assist doctors in performing IVFS. A deep learning-based aorta segmentation algorithm is used to achieve automatic and rapid aorta segmentation. The Vuforia-based virtual-real registration and marker recognition algorithm are integrated to ensure accurate in situ AR image.
The proposed method can provide three-dimensional in situ AR image, and the fiducial registration error after virtual-real registration is 2.070 mm. The aorta segmentation experiment obtains dice similarity coefficient of 91.12% and Hausdorff distance of 2.59, better than conventional algorithms before improvement.
The proposed method can intuitively and accurately locate fenestration positions, and therefore can assist doctors in performing IVFS.
■我们提出了一种AR导航方法,以协助医生进行IVFS。采用基于深度学习的主动脉分割算法实现了主动脉的自动快速分割。集成了基于Vuforia的虚实配准和标记识别算法,以确保准确的原位AR图像。
■所提出的方法可以提供三维原位AR图像,虚实配准后的基准配准误差为2.070mm。主动脉分割实验获得的骰子相似系数为91.12%,Hausdorff距离为2.59,优于改进前的常规算法。
■所提出的方法可以直观,准确地定位开窗位置,因此可以协助医生进行IVFS。