PDF(Sci-hub)
Abstract：
Soft-tissue deformation represents a significant error source in current surgical navigation systems used for open hepatic procedures. While numerous algorithms have been proposed to rectify the tissue deformation that is encountered during open liver surgery, clinical validation of the proposed methods has been limited to surface-based metrics, and subsurface validation has largely been performed via phantom experiments. The proposed method involves the analysis of two deformation-correction algorithms for open hepatic image-guided surgery systems via subsurface targets digitized with tracked intraoperative ultrasound (iUS). Intraoperative surface digitizations were acquired via a laser range scanner and an optically tracked stylus for the purposes of computing the physical-to-image space registration and for use in retrospective deformation-correction algorithms. Upon completion of surface digitization, the organ was interrogated with a tracked iUS transducer where the iUS images and corresponding tracked locations were recorded. Mean closest-point distances between the feature contours delineated in the iUS images and corresponding three-dimensional anatomical model generated from preoperative tomograms were computed to quantify the extent to which the deformation-correction algorithms improved registration accuracy. The results for six patients, including eight anatomical targets, indicate that deformation correction can facilitate reduction in target error of [Formula: see text].
摘要：
软组织变形代表了当前用于开放肝脏手术的手术导航系统中的重大误差源。虽然已经提出了许多算法来纠正在开放肝脏手术中遇到的组织变形，所提出方法的临床验证仅限于基于表面的指标，地下验证主要是通过体模实验进行的。所提出的方法涉及通过用跟踪术中超声（iUS）数字化的地下目标分析开放式肝脏图像引导的手术系统的两种变形校正算法。为了计算物理到图像空间的配准并用于回顾性变形校正算法，通过激光测距扫描仪和光学跟踪的触控笔获取了术中表面数字化。表面数字化完成后，用追踪的iUS传感器询问器官,记录了iUS图像和相应的追踪位置.计算iUS图像中描绘的特征轮廓与根据术前断层照片生成的相应三维解剖模型之间的平均最近点距离，以量化变形校正算法提高配准准确性的程度。6名患者的结果，包括八个解剖目标，表明变形校正有助于减少[公式：见正文]的目标误差。
