Computer- and robot-assisted Medical Intervention

Medical robotics includes assistive devices used by the physician in order to make his/her diagnostic or therapeutic practices easier and more efficient. This chapter focuses on such systems. It introduces the general field of Computer-Assisted Medical Interventions, its aims, its different components and describes the place of robots in that context. The evolutions in terms of general design and control paradigms in the development of medical robots are presented and issues specific to that application domain are discussed. A view of existing systems, on-going developments and future trends is given. A case-study is detailed. Other types of robotic help in the medical environment (such as for assisting a handicapped person, for rehabilitation of a patient or for replacement of some damaged/suppressed limbs or organs) are out of the scope of this chapter.Comment: Handbook of Automation, Shimon Nof (Ed.) (2009) 000-00

Augmented Reality-based Feedback for Technician-in-the-loop C-arm Repositioning

Interventional C-arm imaging is crucial to percutaneous orthopedic procedures as it enables the surgeon to monitor the progress of surgery on the anatomy level. Minimally invasive interventions require repeated acquisition of X-ray images from different anatomical views to verify tool placement. Achieving and reproducing these views often comes at the cost of increased surgical time and radiation dose to both patient and staff. This work proposes a marker-free "technician-in-the-loop" Augmented Reality (AR) solution for C-arm repositioning. The X-ray technician operating the C-arm interventionally is equipped with a head-mounted display capable of recording desired C-arm poses in 3D via an integrated infrared sensor. For C-arm repositioning to a particular target view, the recorded C-arm pose is restored as a virtual object and visualized in an AR environment, serving as a perceptual reference for the technician. We conduct experiments in a setting simulating orthopedic trauma surgery. Our proof-of-principle findings indicate that the proposed system can decrease the 2.76 X-ray images required per desired view down to zero, suggesting substantial reductions of radiation dose during C-arm repositioning. The proposed AR solution is a first step towards facilitating communication between the surgeon and the surgical staff, improving the quality of surgical image acquisition, and enabling context-aware guidance for surgery rooms of the future. The concept of technician-in-the-loop design will become relevant to various interventions considering the expected advancements of sensing and wearable computing in the near future

Extrinsic Parameter Calibration for Line Scanning Cameras on Ground Vehicles with Navigation Systems Using a Calibration Pattern

Line scanning cameras, which capture only a single line of pixels, have been increasingly used in ground based mobile or robotic platforms. In applications where it is advantageous to directly georeference the camera data to world coordinates, an accurate estimate of the camera's 6D pose is required. This paper focuses on the common case where a mobile platform is equipped with a rigidly mounted line scanning camera, whose pose is unknown, and a navigation system providing vehicle body pose estimates. We propose a novel method that estimates the camera's pose relative to the navigation system. The approach involves imaging and manually labelling a calibration pattern with distinctly identifiable points, triangulating these points from camera and navigation system data and reprojecting them in order to compute a likelihood, which is maximised to estimate the 6D camera pose. Additionally, a Markov Chain Monte Carlo (MCMC) algorithm is used to estimate the uncertainty of the offset. Tested on two different platforms, the method was able to estimate the pose to within 0.06 m / 1.05$^{\circ}$ and 0.18 m / 2.39$^{\circ}$. We also propose several approaches to displaying and interpreting the 6D results in a human readable way.Comment: Published in MDPI Sensors, 30 October 201

Robotic-assisted internal fixation of hip fractures: a fluoroscopy-based intraoperative registration technique

The internal fixation of proximal femoral (hip) fractures is the most frequently performed orthopaedic surgery procedure. When using a sliding compression hip screw, a commonly used fixation device, accurate positioning of the device within the femoral neck-head is achieved by initially drilling a pilot hole. A cannulated component of the hip screw is then inserted over the guide wire (surgical drill bit), which is used to drill the pilot hole. However, in practice, this fluoroscopically controlled drilling process is severely complicated by a depth perception problem and, as such, a surgeon can require several attempts to achieve a satisfactory guide wire placement. A prototype robotic-assisted orthopaedic surgery system has therefore been developed, with a view to achieving accurate right-first-time guide wire insertions. This paper describes the non-invasive digital X-ray photogrammetry-based registration technique which supports the proposed robotic-assisted drilling scenario. Results from preliminary laboratory (in vitro) trials employing this registration technique indicate that the cumulative error associated with the entire X-ray guided robotic system is within acceptable limits for the guide wire insertion process

SYSTEM INTEGRATION OF C-ARM ROBOTIC PROTOTYPE USING MOTION CAPTURE GUIDANCE FOR ACCURATE REPOSITIONING

One of the important surgical tools in spinal surgery is the C-Arm X-ray System. The C-Arm is a large “C” shaped and manually maneuvered arm that provides surgeons and X-ray technicians the ability to take quick quality X-rays during surgery. Because of its five degrees of freedom, the C-Arm can be manually maneuvered around the patient to provide many angles and perspectives, ensuring surgical success. This system works fine for most surgical procedures but falls short when the C-Arm must be moved out of the way for complicated surgical procedures. The aim of this thesis is to develop an accurate repositioning method with the use of motion capture technology. This will be a novel approach to creating a repositioning integrated system. To develop a motion capture repositioning integrated system, a set of research tasks needed to be completed. A virtual prototype and a virtual platform were developed that quantified the dynamics of the C-Arm maneuvering. Next, a complete kinematic model of the C-Arm was developed. Third, a fully automatic robotic C-Arm prototype was designed and manufactured to serve as a replacement for the actual C-Arm. Finally, the robotic prototype, the virtual platform, and the kinematic model were all systematically integrated using Vicon motion capture system to perform the automatic repositioning of the C-Arm. Testing of the newly developed repositioning system was completed with successful results

Robot Autonomy for Surgery

Autonomous surgery involves having surgical tasks performed by a robot operating under its own will, with partial or no human involvement. There are several important advantages of automation in surgery, which include increasing precision of care due to sub-millimeter robot control, real-time utilization of biosignals for interventional care, improvements to surgical efficiency and execution, and computer-aided guidance under various medical imaging and sensing modalities. While these methods may displace some tasks of surgical teams and individual surgeons, they also present new capabilities in interventions that are too difficult or go beyond the skills of a human. In this chapter, we provide an overview of robot autonomy in commercial use and in research, and present some of the challenges faced in developing autonomous surgical robots

Spherical acquisition trajectories for X-ray computed tomography with a robotic sample holder

This work presents methods for the seamless execution of arbitrary spherical trajectories with a seven-degree-of-freedom robotic arm as a sample holder. The sample holder is integrated into an existing X-ray computed tomography setup. We optimized the path planning and robot control algorithms for the seamless execution of spherical trajectories. A precision-manufactured sample holder part is attached to the robotic arm for the calibration procedure. Different designs of this part are tested and compared to each other for optimal coverage of trajectories and reconstruction image quality. We present experimental results with the robotic sample holder where a sample measurement on a spherical trajectory achieves improved reconstruction quality compared to a conventional circular trajectory. Our results demonstrate the superiority of the discussed system as it outperforms single-axis systems by reaching nearly 82\% of all possible rotations. The proposed system is a step towards higher image reconstruction quality in flexible X-ray CT systems. It will enable reduced scan times and radiation dose exposure with task-specific trajectories in the future, as it can capture information from various sample angles