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使用图像约束生物力学模型的机器人手术动态引导

Dynamic guidance for robotic surgery using image-constrained biomechanical models.

作者信息

Pratt Philip, Stoyanov Danail, Visentini-Scarzanella Marco, Yang Guang-Zhong

机构信息

Institute of Biomedical Engineering, Imperial College of Science, Technology and Medicine, London SW7 2AZ, UK.

出版信息

Med Image Comput Comput Assist Interv. 2010;13(Pt 1):77-85. doi: 10.1007/978-3-642-15705-9_10.

Abstract

The use of physically-based models combined with image constraints for intraoperative guidance is important for surgical procedures that involve large-scale tissue deformation. A biomechanical model of tissue deformation is described in which surface positional constraints and internally generated forces are derived from endoscopic images and preoperative 4D CT data, respectively. Considering cardiac motion, a novel technique is presented which minimises the average registration error over one or more complete cycles. Features tracked in the stereo video stream provide surface constraints, and an inverse finite element simulation is presented which allows internal forces to be recovered from known preoperative displacements. The accuracy of surface texture, segmented mesh and volumetrically rendered overlays is evaluated with detailed phantom experiments. Results indicate that by combining preoperative and intraoperative images in this manner, accurate intraoperative tissue deformation modelling can be achieved.

摘要

将基于物理的模型与图像约束相结合用于术中引导,对于涉及大规模组织变形的外科手术至关重要。本文描述了一种组织变形的生物力学模型,其中表面位置约束和内部产生的力分别从内窥镜图像和术前4D CT数据中得出。考虑到心脏运动,提出了一种新技术,该技术可使一个或多个完整周期内的平均配准误差最小化。立体视频流中跟踪的特征提供表面约束,并提出了一种逆有限元模拟方法,该方法可从已知的术前位移中恢复内力。通过详细的体模实验评估了表面纹理、分割网格和体积渲染叠加的准确性。结果表明,通过以这种方式组合术前和术中图像,可以实现准确的术中组织变形建模。

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