1,961 research outputs found
Autonomous Tissue Scanning under Free-Form Motion for Intraoperative Tissue Characterisation
In Minimally Invasive Surgery (MIS), tissue scanning with imaging probes is
required for subsurface visualisation to characterise the state of the tissue.
However, scanning of large tissue surfaces in the presence of deformation is a
challenging task for the surgeon. Recently, robot-assisted local tissue
scanning has been investigated for motion stabilisation of imaging probes to
facilitate the capturing of good quality images and reduce the surgeon's
cognitive load. Nonetheless, these approaches require the tissue surface to be
static or deform with periodic motion. To eliminate these assumptions, we
propose a visual servoing framework for autonomous tissue scanning, able to
deal with free-form tissue deformation. The 3D structure of the surgical scene
is recovered and a feature-based method is proposed to estimate the motion of
the tissue in real-time. A desired scanning trajectory is manually defined on a
reference frame and continuously updated using projective geometry to follow
the tissue motion and control the movement of the robotic arm. The advantage of
the proposed method is that it does not require the learning of the tissue
motion prior to scanning and can deal with free-form deformation. We deployed
this framework on the da Vinci surgical robot using the da Vinci Research Kit
(dVRK) for Ultrasound tissue scanning. Since the framework does not rely on
information from the Ultrasound data, it can be easily extended to other
probe-based imaging modalities.Comment: 7 pages, 5 figures, ICRA 202
Robotic Ultrasound Imaging: State-of-the-Art and Future Perspectives
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
Learning Ultrasound Scanning Skills from Human Demonstrations
Recently, the robotic ultrasound system has become an emerging topic owing to
the widespread use of medical ultrasound. However, it is still a challenging
task to model and to transfer the ultrasound skill from an ultrasound
physician. In this paper, we propose a learning-based framework to acquire
ultrasound scanning skills from human demonstrations. First, the ultrasound
scanning skills are encapsulated into a high-dimensional multi-modal model in
terms of interactions among ultrasound images, the probe pose and the contact
force. The parameters of the model are learned using the data collected from
skilled sonographers' demonstrations. Second, a sampling-based strategy is
proposed with the learned model to adjust the extracorporeal ultrasound
scanning process to guide a newbie sonographer or a robot arm. Finally, the
robustness of the proposed framework is validated with the experiments on real
data from sonographers
Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review
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
Robotic-assisted ultrasound for fetal imaging: Evolution from single-arm to dual-arm system
© Springer Nature Switzerland AG 2019. The development of robotic-assisted extracorporeal ultrasound systems has a long history and a number of projects have been proposed since the 1990s focusing on different technical aspects. These aim to resolve the deficiencies of on-site manual manipulation of hand-held ultrasound probes. This paper presents the recent ongoing developments of a series of bespoke robotic systems, including both single-arm and dual-arm versions, for a project known as intelligent Fetal Imaging and Diagnosis (iFIND). After a brief review of the development history of the extracorporeal ultrasound robotic system used for fetal and abdominal examinations, the specific aim of the iFIND robots, the design evolution, the implementation details of each version, and the initial clinical feedback of the iFIND robot series are presented. Based on the preliminary testing of these newly-proposed robots on 42 volunteers, the successful and reliable working of the mechatronic systems were validated. Analysis of a participant questionnaire indicates a comfortable scanning experience for the volunteers and a good acceptance rate to being scanned by the robots
Development of a real-time ultrasonic sensing system for automated and robotic welding
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The implementation of robotic technology into welding processes is made difficult by the inherent process variables of part location, fit up, orientation and repeatability. Considering these aspects, to ensure weld reproducibility consistency and quality, advanced adaptive control techniques are essential. These involve not only the development of adequate sensors for seam tracking and joint recognition but also developments of overall machines with a level of artificial intelligence sufficient for automated welding.
The development of such a prototype system which utilizes a manipulator arm, ultrasonic sensors and a transistorised welding power source is outlined. This system incorporates three essential aspects. It locates and tracks the welding seam ensuring correct positioning of the welding head relatively to the joint preparation. Additionally, it monitors the joint profile of the molten weld pool and modifies the relevant heat input parameters ensuring consistent penetration, joint filling and acceptable weld bead shape. Finally, it makes use of both the above information to reconstruct three-dimensional images of the weld pool silhouettes providing in-process inspection capabilities of the welded joints.
Welding process control strategies have been incorporated into the system based on quantitative relationships between input parameters and weld bead shape configuration allowing real-time decisions to be made during the process of welding, without the need for operation intervention.British Technology Group (BTG
APP-RUSS: Automated Path Planning for Robotic Ultrasound System
Autonomous robotic ultrasound System (RUSS) has been extensively studied.
However, fully automated ultrasound image acquisition is still challenging,
partly due to the lack of study in combining two phases of path planning:
guiding the ultrasound probe to the scan target and covering the scan surface
or volume. This paper presents a system of Automated Path Planning for RUSS
(APP-RUSS). Our focus is on the first phase of automation, which emphasizes
directing the ultrasound probe's path toward the target over extended
distances. Specifically, our APP-RUSS system consists of a RealSense D405 RGB-D
camera that is employed for visual guidance of the UR5e robotic arm and a cubic
Bezier curve path planning model that is customized for delivering the probe to
the recognized target. APP-RUSS can contribute to understanding the integration
of the two phases of path planning in robotic ultrasound imaging, paving the
way for its clinical adoption
- …