1,411 research outputs found

    Robot Autonomy for Surgery

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    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

    Computer- and robot-assisted Medical Intervention

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    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

    Medical Robotics

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    The first generation of surgical robots are already being installed in a number of operating rooms around the world. Robotics is being introduced to medicine because it allows for unprecedented control and precision of surgical instruments in minimally invasive procedures. So far, robots have been used to position an endoscope, perform gallbladder surgery and correct gastroesophogeal reflux and heartburn. The ultimate goal of the robotic surgery field is to design a robot that can be used to perform closed-chest, beating-heart surgery. The use of robotics in surgery will expand over the next decades without any doubt. Minimally Invasive Surgery (MIS) is a revolutionary approach in surgery. In MIS, the operation is performed with instruments and viewing equipment inserted into the body through small incisions created by the surgeon, in contrast to open surgery with large incisions. This minimizes surgical trauma and damage to healthy tissue, resulting in shorter patient recovery time. The aim of this book is to provide an overview of the state-of-art, to present new ideas, original results and practical experiences in this expanding area. Nevertheless, many chapters in the book concern advanced research on this growing area. The book provides critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies. This book is certainly a small sample of the research activity on Medical Robotics going on around the globe as you read it, but it surely covers a good deal of what has been done in the field recently, and as such it works as a valuable source for researchers interested in the involved subjects, whether they are currently “medical roboticists” or not

    Using ultrasound images of the forearm to predict finger positions

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    Shared control for natural motion and safety in hands-on robotic surgery

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    Hands-on robotic surgery is where the surgeon controls the tool's motion by applying forces and torques to the robot holding the tool, allowing the robot-environment interaction to be felt though the tool itself. To further improve results, shared control strategies are used to combine the strengths of the surgeon with those of the robot. One such strategy is active constraints, which prevent motion into regions deemed unsafe or unnecessary. While research in active constraints on rigid anatomy has been well-established, limited work on dynamic active constraints (DACs) for deformable soft tissue has been performed, particularly on strategies which handle multiple sensing modalities. In addition, attaching the tool to the robot imposes the end effector dynamics onto the surgeon, reducing dexterity and increasing fatigue. Current control policies on these systems only compensate for gravity, ignoring other dynamic effects. This thesis presents several research contributions to shared control in hands-on robotic surgery, which create a more natural motion for the surgeon and expand the usage of DACs to point clouds. A novel null-space based optimization technique has been developed which minimizes the end effector friction, mass, and inertia of redundant robots, creating a more natural motion, one which is closer to the feeling of the tool unattached to the robot. By operating in the null-space, the surgeon is left in full control of the procedure. A novel DACs approach has also been developed, which operates on point clouds. This allows its application to various sensing technologies, such as 3D cameras or CT scans and, therefore, various surgeries. Experimental validation in point-to-point motion trials and a virtual reality ultrasound scenario demonstrate a reduction in work when maneuvering the tool and improvements in accuracy and speed when performing virtual ultrasound scans. Overall, the results suggest that these techniques could increase the ease of use for the surgeon and improve patient safety.Open Acces

    Biomechanical Modeling and Inverse Problem Based Elasticity Imaging for Prostate Cancer Diagnosis

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    Early detection of prostate cancer plays an important role in successful prostate cancer treatment. This requires screening the prostate periodically after the age of 50. If screening tests lead to prostate cancer suspicion, prostate needle biopsy is administered which is still considered as the clinical gold standard for prostate cancer diagnosis. Given that needle biopsy is invasive and is associated with issues including discomfort and infection, it is desirable to develop a prostate cancer diagnosis system that has high sensitivity and specificity for early detection with a potential to improve needle biopsy outcome. Given the complexity and variability of prostate cancer pathologies, many research groups have been pursuing multi-parametric imaging approach as no single modality imaging technique has proven to be adequate. While imaging additional tissue properties increases the chance of reliable prostate cancer detection and diagnosis, selecting an additional property needs to be done carefully by considering clinical acceptability and cost. Clinical acceptability entails ease with respect to both operating by the radiologist and patient comfort. In this work, effective tissue biomechanics based diagnostic techniques are proposed for prostate cancer assessment with the aim of early detection and minimizing the numbers of prostate biopsies. The techniques take advantage of the low cost, widely available and well established TRUS imaging method. The proposed techniques include novel elastography methods which were formulated based on an inverse finite element frame work. Conventional finite element analysis is known to have high computational complexity, hence computation time demanding. This renders the proposed elastography methods not suitable for real-time applications. To address this issue, an accelerated finite element method was proposed which proved to be suitable for prostate elasticity reconstruction. In this method, accurate finite element analysis of a large number of prostates undergoing TRUS probe loadings was performed. Geometry input and displacement and stress fields output obtained from the analysis were used to train a neural network mapping function to be used for elastopgraphy imaging of prostate cancer patients. The last part of the research presented in this thesis tackles an issue with the current 3D TRUS prostate needle biopsy. Current 3D TRUS prostate needle biopsy systems require registering preoperative 3D TRUS to intra-operative 2D TRUS images. Such image registration is time-consuming while its real-time implementation is yet to be developed. To bypass this registration step, concept of a robotic system was proposed which can reliably determine the preoperative TRUS probe position relative to the prostate to place at the same position relative to the prostate intra-operatively. For this purpose, a contact pressure feedback system is proposed to ensure similar prostate deformation during 3D and 2D image acquisition in order to bypass the registration step

    Robotic Ultrasound Imaging: State-of-the-Art and Future Perspectives

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    Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques.Comment: Accepted by Medical Image Analysi

    Intraoperative Navigation Systems for Image-Guided Surgery

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    Recent technological advancements in medical imaging equipment have resulted in a dramatic improvement of image accuracy, now capable of providing useful information previously not available to clinicians. In the surgical context, intraoperative imaging provides a crucial value for the success of the operation. Many nontrivial scientific and technical problems need to be addressed in order to efficiently exploit the different information sources nowadays available in advanced operating rooms. In particular, it is necessary to provide: (i) accurate tracking of surgical instruments, (ii) real-time matching of images from different modalities, and (iii) reliable guidance toward the surgical target. Satisfying all of these requisites is needed to realize effective intraoperative navigation systems for image-guided surgery. Various solutions have been proposed and successfully tested in the field of image navigation systems in the last ten years; nevertheless several problems still arise in most of the applications regarding precision, usability and capabilities of the existing systems. Identifying and solving these issues represents an urgent scientific challenge. This thesis investigates the current state of the art in the field of intraoperative navigation systems, focusing in particular on the challenges related to efficient and effective usage of ultrasound imaging during surgery. The main contribution of this thesis to the state of the art are related to: Techniques for automatic motion compensation and therapy monitoring applied to a novel ultrasound-guided surgical robotic platform in the context of abdominal tumor thermoablation. Novel image-fusion based navigation systems for ultrasound-guided neurosurgery in the context of brain tumor resection, highlighting their applicability as off-line surgical training instruments. The proposed systems, which were designed and developed in the framework of two international research projects, have been tested in real or simulated surgical scenarios, showing promising results toward their application in clinical practice

    Robotic Ultrasound Tomography and Collaborative Control

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    Ultrasound computed tomography (USCT) offers quantitative anatomical tissue characterization for cancer detection, and has shown similar diagnostic power to MRI on ex vivo prostate tissue. While most USCT research and commercial development has focused on submerging target anatomy in a transducer-lined cylindrical water-tank, this approach is not practical for imaging deep anatomy like the prostate and an alternative acquisition system using aligned abdominal and endolumenal ultrasound probes is required. This work outlines a clinical workflow, calibration scheme, and motion framework for an innovative dual-robotic USCT acquisition system specific to in vivo prostate imaging – one arm wielding a linear abdominal probe, the other wielding a linear transrectal ultrasound (TRUS) probe. After a three-way calibration, the robotic system works to autonomously keep the abdominal probe collinear with the physician-rotated TRUS probe using a hybrid force-position convex contour tracking scheme, while impedance control enforces its gentle contact with the patient’s pubic region for capturing the transmission ultrasound slices needed for limited-angle tomographic reconstruction. TRUS rotation was induced by joystick control for precision during testing, however collaborative control via admittance control of hand forces presents a useful workflow option to the physician. An improved robot admittance control algorithm for transparent collaborative control utilizing Kalman filtering was developed and verified to smooth robot hand guidance. Such an improvement additionally has important implications for generally alleviating ultrasonographer musculoskeletal strain through cooperatively controlled robots. The ultimate dual-robotic USCT system proved repeatable and sufficiently accurate for tomography based on pelvic phantom testing. Future steps in system verification and validation are discussed, as is incorporation into feasibility studies to test the potential and utility of the system for future prostate malignancy diagnosis and staging in vivo
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