基于二维超声- 三维 CT 配准的肾脏穿刺定位方法可行性研究

医学影像引导的经皮肾穿刺手术是经皮肾镜取石术中建立手术通道的重要手段,高质量的 实时医学图像可以提高术中穿刺精度,减少手术风险。针对自由呼吸下经皮肾穿刺靶点的导航定位问 题,该研究提出了一种基于术中二维超声-术前三维 CT 实时配准的肾脏穿刺定位方法。首先对肾脏轮 廓特征的二维超声图像和三维 CT 图像进行由粗到精的快速配准,然后通过超声探头标定,将配准融合 后的图像注册到手术空间,实现穿刺靶点的实时定位。人体腹部模型实验结果表明,超声探头标定均 方根误差为 0.998 mm,二维超声和三维 CT 数据配准误差为 0.709 mm,平均配准运算时间为 1.15 s,最 终的平均定位误差为 2.265 mm。     

基于超声影像导航的肝癌消融机器人系统的误差传递

建立了基于超声影像导航的肝癌消融机器人系统误差传递模型．该系统主要由超声影像设备、导航 软件子系统、定位装置和穿刺机器人四个模块组成．机器人系统首先通过三维超声重建、术前模型和术中实体的 配准以及定位装置和机器人之间的坐标转换将肿瘤的目标靶点转化到机器人坐标系中,然后再控制机器人运动到 指定的靶点位置进行治疗．首先分析上述流程,指出误差源．然后,利用齐次变换矩阵的微分矩阵建立靶点映射 误差传递模型,并通过仿真实验验证了靶点误差模型的正确性．最后,对系统进行了精度测试实验,实验结果表 明该系统的总体误差小于5 mm,满足消融治疗肝癌的需求,能有效地提高肝癌的治疗效果．     

颅颌面外科手术机器人空间配准及实验

针对颅颌面区域结构复杂、手术风险大、精度要求高的特点,研发了一套颅颌面外科手术机器人系统．为实现机器人系统高效、精确的空间配准,提出并建立了一套基于光学定位的颅颌面外科手术机器人空间配准方法,实现了机器人各子系统之间的坐标系转换．通过基于四元数的最近点迭代配准算法实现了点集之间的矩阵转换．在综合医学影像、机器人与各子系统空间配准的基础上,分别开展了配准精度和定位精度的验证实验,并完成了三叉神经射频热凝术的模型和尸体穿刺定位实验．配准精度验证实验的配准误差平均值均小于0.75mm,定位精度验证实验的误差平均值为0.56mm,模型实验的穿刺成功率为100%,尸体实验的穿刺成功率为95%．综合实验结果表明该空间配准方法的配准精度较高,具有一定的可行性,可以满足颅颌面外科手术机器人系统的需要．     

基于解剖标记点的手术导航空间配准研究

空间配准是手术导航系统最为关键的技术。点匹配空间配准需要专门为导航进行一次图像扫描，增加了病人的辐射剂量和手术成本，面匹配空间配准因扫描仪扫描范围有限而导致配准精度不均匀，无法在临床上广泛应用。本文提出一种基于解剖标记点的空间配准方法，无须在病人头部粘贴人工标记物，且靶点配准误差相对较小。实验结果表明，该方法的靶点配准误差（Target Registration Error, TRE）均小于2.5mm，能够满足临床应用。     

基于Kinect的机器人辅助超声扫描系统研究

提出一种采用Kinect传感器作为视觉伺服的机器人辅助超声扫描系统,来规划引导机器人的扫描路线,以实现机器人辅助的超声扫描操作。系统由Kinect传感器、机器人和超声探头组成。采用Kinect实时获取超声探头的RGB图像和深度图像,并计算探头当前位姿,结合坐标系配准结果,得到机器人的位姿信息,再根据术前的机器人轨迹规划,引导机器人的超声扫描路径。开展腿部模型实验验证本系统的可行性,通过对Kinect传感器的相机标定实验,计算得到了RGB相机和深度相机的内外参数,通过对探头上标识物的定位,进而计算出探头当前位姿,结合Kinect与机器人坐标系的配准结果,得到了两者的转换矩阵,并对机器人的位置给出指令,引导机械臂夹持探头到达指定扫描位置。在机器人夹持超声探头扫描过程中,实时计算探头与腿部之间的距离,以保证所采集超声图像的质量及扫描操作的安全性。实验结果表明,在Kinect视觉系统的导航引导下,机器人可以夹持超声探头实现自主超声扫描,以减少超声医师的扫描时间,降低医师的劳动强度。     

基于正侧位投影约束的空间配准与脊柱手术导航

为提高机器人辅助脊柱手术的精确性、安全性以及易用性,将术前CT 图像与术中X 射线图像配准． 传统单平面配准法因缺乏沿光轴的深度信息而导致导航误差较大,本文通过同时计算正侧位透视图像来提高配准与 导航精度．通过分析正侧位投影空间变换模型,利用该双平面几何约束实现自动的配准初值估计并建立3 维手术空 间与CT 空间的映射．在虚拟X 射线导航基础上,利用立体视觉定位计算手术器械在CT 空间的实时位姿从而实现 3 维导航．脊柱体模实验证明该配准与导航方法的精度满足手术要求,动物椎板磨削实验表明该系统可实现实时监 控,提高手术安全性．     

面向Kinect RGB-D图像的目标尺寸测量方法

利用图像测量物体尺寸是一种非接触式测量方法。利用微软公司的Kinect相机能获取RGB-D图像的特点,完成了一种非接触式测量方法。并对Kinect相机的测量深度图误差进行了大量实际测量实验得出相关结论,针对Kinect的深度图特点,建立了非接触式测量的相机几何模型,并标定出几何模型的参数,利用所得的参数实际测量、验证并分析了系统的误差,完成了Kinect相机非接触式测量的方法,实现非接触式测量误差约为1mm。     

面向室内动态场景的多传感视觉SLAM方法

针对传统同时定位与地图构建(simultaneous localization and mapping,SLAM)框架面临动态场景时产生明显定位误差,建立的场景稠密地图会包含动态对象及其运动叠影,从而导致定位与建图鲁棒性不足的问题,面向以人类为主要动态对象的室内动态场景,从“温度”的角度出发,提出基于热像仪与深度相机结合的多传感SLAM协同方案,解决室内动态场景中的定位与建图难题。首先,建立一套针对热像仪与深度相机的联合标定策略,重新设计标定板与标定方案,完成相机的内参标定、外参标定与图像配准,得到一一对应的RGB、深度、热(RDH)三模图像;其次,由热图像得到人体掩模图像,进而在ORB-SLAM2系统框架下构建静态特征提取与数据关联策略,实现基于三模图像的视觉里程计;然后,基于人体掩模图像更新深度图像,滤除人体区域,进而完成基于三模图像的静态环境稠密地图构建;最后,在室内动态场景下进行实验验证,结果表明所提出算法在室内动态场景下可有效剔除动态对象的干扰特征,相对传统SLAM算法具有明显优势。     

协同定位中的坐标配准策略研究

坐标配准是协同定位的重要组成部分,一个合理的坐标配准体系可以体现协同定位算法的性能,否则可能会放大定位算法的误差。本文详细比较了基于最小二乘 (least square, LS)与基于普氏分析(Procrustes analysis, PA)的配准方法的设计思想、适用条件,并给出了基于普氏分析的坐标配准算法的详细步骤。利用协同定位算法(经典MDS和Levenberg–Marquardt算法)得到的实验数据,详细分析了锚节点数量、测距误差、网络节点平均连通度对配准精度的影响。实验表明,在2D和3D环境中,基于普氏分析的配准算法,其配准精度和稳定性都优于最小二乘法,配准误差降低约为20%。     

基于Cortex-M4的多传感器组合导航系统设计

针对移动机器人导航定位需求,设计了一种低成本、便携式的多传感器组合导航系统.采用ARM Cortex-M4内核的STM32F407处理器为电路核心,利用微惯性测量单元(MIMU)、全球卫星定位系统(GPS)以及电子罗盘作为导航数据源,进行了相关的硬件设计;采用移动导航平台进行实验验证,通过实测数据进行分析,结果表明:该组合导航系统可以有效提高导航精度,使其导航定位经纬度误差稳定在1.0m左右,航向角误差稳定在0.8°以内,对移动机器人导航有一定的参考价值.     

Development of a slender continuum robotic system for on-wing inspection/repair of gas turbine engines

The maintenance works (e.g. inspection, repair) of aero-engines while still attached on the airframes requires a desirable approach since this can significantly shorten both the time and cost of such interventions as the aerospace industry commonly operates based on the generic concept “power by the hour”. However, navigating and performing a multi-axis movement of an end-effector in a very constrained environment such as gas turbine engines is a challenging task. This paper reports on the development of a highly flexible slender (i.e. low diameter-to-length ratios) continuum robot of 25 degrees of freedom capable to uncoil from a drum to provide the feeding motion needed to navigate into crammed environments and then perform, with its last 6 DoF, complex trajectories with a camera equipped machining end-effector for allowing in-situ interventions at a low-pressure compressor of a gas turbine engine. This continuum robot is a compact system and presents a set of innovative mechatronics solutions such as: (i) twin commanding cables to minimise the number of actuators; (ii) twin compliant joints to enable large bending angles (±90°) arranged on a tapered structure (start from 40 mm to 13 mm at its end); (iii) feeding motion provided by a rotating drum for coiling/uncoiling the continuum robot; (iv) machining end-effector equipped with vision system. To be able to achieve the in-situ maintenance tasks, a set of innovative control algorithms to enable the navigation and end-effector path generation have been developed and implemented. Finally, the continuum robot has been tested both for navigation and movement of the end-effector against a specified target within a gas turbine engine mock-up proving that: (i) max. deviations in navigation from the desired path (1000 mm length with bends between 45° and 90°) are ±10 mm; (ii) max. errors in positioning the end-effector against a target situated at the end of navigation path is 1 mm. Thus, this paper presents a compact continuum robot that could be considered as a step forward in providing aero-engine manufacturers with a solution to perform complex tasks in an invasive manner.     

Registration errors in beacon-based navigation guidance systems: Influences on path efficiency and user reliance

Emerging augmented reality displays provide high fidelity overlays onto real-world environments to enable navigation efficiency. The accuracy of these systems, however, is highly contingent on monitoring and registering user orientations and landmark locations. No data exist, however, regarding ranges at which registration error reliably influences user behavior and trust. The present experiments examined the influence of directional error in a simulated navigation guidance system on path efficiency and user trust. In three experiments, participants (N=90) navigated an urban desktop virtual environment with the assistance of an overlaid beacon depicting the direction and distance of a target landmark. Directional error was introduced into the beacon across trials, manipulated in 15° increments from 0° to 60° (Experiment 1), 5° increments from 0° to 20° (Experiment 2), and 1° increments from 6° to 10° (Experiment 3). Users show tolerance for up to approximately 8° angular direction error without significantly reducing path efficiency or user trust in system reliability. They also show reduced path efficiency emerging at lower angular errors (approximately 9°) relative to influences on perceived trust (approximately 16–20°). Results provide some basic heuristics for error tolerance, demonstrate important dissociations between the objective versus perceived impact of error in navigation displays, and contribute to theoretical positions regarding the optimization of global awareness and spatial knowledge acquisition.     

基于Kinect传感器和ORB特征的视觉SLAM算法设计与实现

介绍了一个基于嵌入式平台和Kinect传感器的同时定位与地图创建算法的设计与实现。Kinect传感器包括一个可见光彩色摄像头和一个利用结构光测量深度的红外CMOS摄像头。 算法利用ORB算子作为环境特征点的描述信息,并利用基于边沿的最近邻修复方法对深度图像进行修正以获得完整的深度信息。在此基础上,利用LSH方法进行特征点的匹配。实验结果表明,基于ORB特征的视觉SLAM算法具有较好的实用性和良好的定位精度,可以广泛应用于室内机器人的自主导航任务。     

Image guided oral implantology and its application in the placement of zygoma implants

The application of zygoma implants proposes a successful treatment for functional reconstruction of maxillary defects. However, the placement of zygoma implants is not without risk due to anatomically complex operation sites. Aiming at minimizing the risks and improving the precision of the surgery, an image guided oral implantology system (IGOIS) is presented in this study to transfer the preoperative plan accurately to the operating theatre. The principle of IGOIS is introduced in detail, including the framework, 3D-reconstruction, preoperative planning, registration, and the motion tracking algorithm. The phantom experiment shows that fiducial registration error (FRE) and TRE (target registration error) of IGOIS are, respectively, 1.12mm and 1.35mm. With respect to the overall accuracy, the average distance deviations at the coronal and apical point of the implant are, respectively, 1.36+/-0.59mm and 1.57+/-0.59mm, while average angle deviation between the axes of the planned and the actual implant is 4.1 degrees +/-0.9 degrees . A clinical report for a patient with a severely atrophic maxilla demonstrates that the major advantage of this computer-aided navigation technology lies in its accuracy, reliability, and flexibility.     

基于VI-SLAM的四翼无人机多目标视觉定位技术

针对传统多目标视觉定位技术定位误差大这一问题,基于VI-SLAM的四旋翼无人机提出了一种新的多目标视觉定位技术,阐述了定位技术原理,在进行定位时,导航定位系统、航空姿态测量系统、机载光电测量平台共同工作,通过多目标相机标定、锁定目标背景差分确定目标在摄像机坐标系的位置,将摄像机坐标系转换成载机机体坐标系,再将载机机体坐标系转换成大地坐标系,从而实现定位,引入北斗卫星导航系统和递归最小二乘算法降低定位误差。对比实验结果表明,相较于传统定位技术,基于VI-SLAM的四旋翼无人机的多目标视觉定位技术定位误差更小,应用性更广。     

基于完整可见性模型的改进鲁棒OctoMap

从移动机器人自主导航对3D地图精度的需求出发,在鲁棒OctoMap的基础上提出一种基于完整可见性模型的改进鲁棒OctoMap并应用于基于Kinect的RGB-D同时定位与地图创建（SLAM）中。首先,通过考虑相机和目标体素的相对位置关系及地图分辨率进行可连通性判断,获得满足可连通性的相邻体素的个数及位置;其次,根据不同的可连通性情况分别建立目标体素的可见性模型,从而构建普适性更强的完整可见性模型,有效克服了鲁棒OctoMap可见性模型的局限性,提高了建图精度;再次,使用基于高斯混合模型的Kinect深度误差模型代替简单深度误差模型,进一步克服传感器测量误差对地图精度的影响,降低了地图的不确定性;最后,结合贝叶斯公式和线性插值算法来更新八叉树中每个节点的实际占用概率,从而构建基于八叉树的立体占用地图。实验结果表明,所提方法有效克服了Kinect传感器深度误差对地图精度的影响,降低了地图的不确定性,其建图精度较鲁棒OctoMap有明显的提高。     

An augmented reality system to guide radio‐frequency tumour ablation

Radio‐frequency ablation is a difficult operative task that requires a precise needle positioning in the centre of the pathology. This article presents an augmented reality system for hepatic therapy guidance that superimposes in real‐time 3D reconstructions (from CT acquisition) and a virtual model of the needle on external views of a patient. The superimposition of reconstructed models is performed with a 3D/2D registration based on radio‐opaque markers stuck on to the patient's skin. The characteristics of the problem (accuracy, robustness and time processing) led us to develop automatic procedures to extract and match the markers and to track the needle in real time. Experimental studies confirmed that our algorithms are robust and reliable. Preliminary experiments conducted on a human abdomen phantom showed that our system is highly accurate (needle positioning error within 3 mm) and enables the surgeon to reach a target in less than 1 minute on average. Our next step will be to perform an in vivo evaluation. Copyright © 2005 John Wiley & Sons, Ltd.     

基于Kinect的改进移动机器人视觉SLAM

针对传统ICP（iterative closest points,迭代最近点算法）存在易陷入局部最优、匹配误差大等问题,提出了一种新的欧氏距离和角度阈值双重限制方法,并在此基础上构建了基于Kinect的室内移动机器人RGB-D SLAM（simultaneous localization and mapping）系统。首先,使用Kinect获取室内环境的彩色信息和深度信息,通过图像特征提取与匹配,结合相机内参与像素点深度值,建立三维点云对应关系;然后,利用RANSAC（random sample consensus）算法剔除外点,完成点云的初匹配;采用改进的点云配准算法完成点云的精匹配;最后,在关键帧选取中引入权重,结合g2o（general graph optimization）算法对机器人位姿进行优化。实验证明该方法的有效性与可行性,提高了三维点云地图的精度,并估计出了机器人运行轨迹。