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Towards an accurate tracking of liver tumors for augmented reality in robotic assisted surgery

机译:在机器人辅助手术中实现肝脏肿瘤的精确跟踪以增强现实

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This article introduces a method for tracking the internal structures of the liver during robot-assisted procedures. Vascular network, tumors and cut planes, computed from pre-operative data, can be overlaid onto the laparoscopic view for image-guidance, even in the case of large motion or deformation of the organ. Compared to current methods, our method is able to precisely propagate surface motion to the internal structures. This is made possible by relying on a fast yet accurate biomechanical model of the liver combined with a robust visual tracking approach designed to properly constrain the model. Augmentation results are demonstrated on in-vivo sequences of a human liver during robotic surgery, while quantitative validation is performed on an ex-vivo porcine liver experimentation. Validation results show that our approach gives an accurate surface registration with an error of less than 6mm on the position of the tumor.
机译:本文介绍了一种在机器人辅助操作过程中跟踪肝脏内部结构的方法。根据术前数据计算出的血管网络,肿瘤和切面,即使在器官运动较大或变形的情况下,也可以覆盖在腹腔镜视图上以进行图像引导。与当前方法相比,我们的方法能够将表面运动精确地传播到内部结构。依靠快速而准确的肝脏生物力学模型,以及旨在适当约束模型的强大视觉跟踪方法,可以实现这一点。在机器人手术期间,在人类肝脏的体内序列上证实了增强结果,而在体外猪肝脏实验中进行了定量验证。验证结果表明,我们的方法能够准确定位表面,肿瘤位置的误差小于6mm。

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