10,262 research outputs found

    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

    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

    INFORMATION TECHNOLOGY FOR NEXT-GENERATION OF SURGICAL ENVIRONMENTS

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    Minimally invasive surgeries (MIS) are fundamentally constrained by image quality,access to the operative field, and the visualization environment on which thesurgeon relies for real-time information. Although invasive access benefits the patient,it also leads to more challenging procedures, which require better skills andtraining. Endoscopic surgeries rely heavily on 2D interfaces, introducing additionalchallenges due to the loss of depth perception, the lack of 3-Dimensional imaging,and the reduction of degrees of freedom.By using state-of-the-art technology within a distributed computational architecture,it is possible to incorporate multiple sensors, hybrid display devices, and3D visualization algorithms within a exible surgical environment. Such environmentscan assist the surgeon with valuable information that goes far beyond what iscurrently available. In this thesis, we will discuss how 3D visualization and reconstruction,stereo displays, high-resolution display devices, and tracking techniques arekey elements in the next-generation of surgical environments

    Medical image computing and computer-aided medical interventions applied to soft tissues. Work in progress in urology

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    Until recently, Computer-Aided Medical Interventions (CAMI) and Medical Robotics have focused on rigid and non deformable anatomical structures. Nowadays, special attention is paid to soft tissues, raising complex issues due to their mobility and deformation. Mini-invasive digestive surgery was probably one of the first fields where soft tissues were handled through the development of simulators, tracking of anatomical structures and specific assistance robots. However, other clinical domains, for instance urology, are concerned. Indeed, laparoscopic surgery, new tumour destruction techniques (e.g. HIFU, radiofrequency, or cryoablation), increasingly early detection of cancer, and use of interventional and diagnostic imaging modalities, recently opened new challenges to the urologist and scientists involved in CAMI. This resulted in the last five years in a very significant increase of research and developments of computer-aided urology systems. In this paper, we propose a description of the main problems related to computer-aided diagnostic and therapy of soft tissues and give a survey of the different types of assistance offered to the urologist: robotization, image fusion, surgical navigation. Both research projects and operational industrial systems are discussed

    Visual object recognition and tracking

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    This invention describes a method for identifying and tracking an object from two-dimensional data pictorially representing said object by an object-tracking system through processing said two-dimensional data using at least one tracker-identifier belonging to the object-tracking system for providing an output signal containing: a) a type of the object, and/or b) a position or an orientation of the object in three-dimensions, and/or c) an articulation or a shape change of said object in said three dimensions

    Review on Image Guided Surgery Systems

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    Nowadays modern imaging techniques can grant an excellent quality 3D images that clearly show the anatomy, vascularity, pathology and active functions of the tissues. The ability to register these preoperative images to each other, to offer a comprehensive information, and later the ability to register the image space to the patient space intraoperatively is the core for the image guided surgery systems (IGS). Other main elements of the system include the process of tracking the surgical tools intraoperatively by reflecting their positions within the 3D image model. In some occasions an intraoperative image may be acquired and registered to the preoperative images to make sure the 3D model used to guide the operation describes the actual situation at surgery time. This survey overviews the history of IGS and discusses the modern system components for a reliable application and gives information about the different applications in medical specialties that benefited from the use of IGS

    Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review

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    Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519

    Passive Resonant Coil Based Fast Registration And Tracking System For Real-Time Mri-Guided Minimally Invasive Surgery

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    This thesis presents a single-slice based fast stereotactic registration and tracking technique along with a corresponding modular system for guiding robotic mechanism or interventional instrument to perform needle-based interventions under live MRI guidance. The system can provide tracking of full 6 degree-of-freedom (DOF) in stereotactic interventional surgery based upon a single, rapidly acquired cross-sectional image. The whole system is constructed with a modular data transmission software framework and mechanical structure so that it supports remote supervision and manipulation between a 3D Matlab tracking user interface (UI) and an existing MRI robot controller by using the OpenIGTLink network communication protocol. It provides better closed-loop control by implementing a feedback output interface to the MRI-guided robot. A new compact fiducial frame design is presented, and the fiducial is wrapped with a passive resonant coil. The coil resonates at the Larmor frequency for 3T MRI to enhance signal strength and enable for rapid imaging. The fiducial can be attached near the distal end of the robot and coaxially with a needle so as to visualize target tissue and track the surgical tool synchronously. The MRI-compatible design of fiducial frame, robust tracking algorithm and modular interface allow this tracking system to be conveniently used on different robots or devices and in different size of MRI bores. Several iterations of the tracking fiducial and passive resonant coils were constructed and evaluated in a Phillips Achieva 3T MRI. To assess accuracy and robustness of the tracking algorithm, 25 groups of images with different poses were successively scanned along specific sequence in and MRI experiment. The translational RMS error along depth is 0.271mm with standard deviation of 0.277mm for totally 100 samples. The overall angular RMS error is less than 0.426 degree with standard deviation of 0.526 degree for totally 150 samples. The passive resonant coils were shown to significantly increase signal intensity in the fiducial relative to the surroundings and provide for rapid imaging with low flip angles

    i3PosNet: Instrument Pose Estimation from X-Ray in temporal bone surgery

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    Purpose: Accurate estimation of the position and orientation (pose) of surgical instruments is crucial for delicate minimally invasive temporal bone surgery. Current techniques lack in accuracy and/or line-of-sight constraints (conventional tracking systems) or expose the patient to prohibitive ionizing radiation (intra-operative CT). A possible solution is to capture the instrument with a c-arm at irregular intervals and recover the pose from the image. Methods: i3PosNet infers the position and orientation of instruments from images using a pose estimation network. Said framework considers localized patches and outputs pseudo-landmarks. The pose is reconstructed from pseudo-landmarks by geometric considerations. Results: We show i3PosNet reaches errors less than 0.05mm. It outperforms conventional image registration-based approaches reducing average and maximum errors by at least two thirds. i3PosNet trained on synthetic images generalizes to real x-rays without any further adaptation. Conclusion: The translation of Deep Learning based methods to surgical applications is difficult, because large representative datasets for training and testing are not available. This work empirically shows sub-millimeter pose estimation trained solely based on synthetic training data.Comment: Accepted at International journal of computer assisted radiology and surgery pending publicatio
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