Out-of-plane visual servoing method for tracking the carotid artery with a robot-assisted ultrasound diagnostic system

Nakadate, Ryu; Solı́s, Jorge; Takanishi, Atsuo; Minagawa, Eiichi; Sugawara, Motoaki; Niki, Kiyomi

doi:10.1109/icra.2011.5979594

Cited by 30 publications

(18 citation statements)

References 15 publications

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“…In [7], Salcudean et al use an ultrasound image correlation algorithm to track the carotid artery, and propose a shared control over the motion of the ultrasound probe. In [10], the out-of-plane translation of the carotid artery is controlled using an intensity-based method. In [11], intensity-based visual servoing of 2D and 3D probes is used to compensate for organ motion.…”

Section: Introductionmentioning

confidence: 99%

Confidence-driven control of an ultrasound probe: Target-specific acoustic window optimization

Chatelain

Krupa

Navab

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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We propose a control framework to optimize the quality of robotic ultrasound imaging while tracking an anatomical target. We use a multitask approach to control the in-plane motion of a convex probe mounted on the end-effector of a robotic arm, based not only on the position of the target in the image, but also on features extracted from an ultrasound confidence map. The resulting control law therefore guarantees a good image quality, while keeping the target aligned with the central ultrasound scan-line. Potential applications of the proposed approach are, for example, teleoperated ultrasound examination, motion compensation for ultrasound-guided interventions, or automatic ultrasound acquisition. We demonstrate our approach with experiments on an ultrasound examination training phantom in motion.

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Section: Introductionmentioning

confidence: 99%

Confidence-driven control of an ultrasound probe: Target-specific acoustic window optimization

Chatelain

Krupa

Navab

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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“…By extracting features from live 2D or 3D images, tracking of various anatomies such as the carotid artery as well as of surgical tools has been achieved based on ultrasound [16,17]. When coupled with a robot control scheme, applications such as organ motion compensation [18] and visibility maintenance in tele-operation [19] become feasible.…”

Section: Related Workmentioning

confidence: 99%

3D ultrasound registration-based visual servoing for neurosurgical navigation

et al. 2017

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Purpose We present a fully image-based visual servoing framework for neurosurgical navigation and needle guidance. The proposed servo-control scheme allows for compensation of target anatomy movements, maintaining high navigational accuracy over time, and automatic needle guide alignment for accurate manual insertions. Method Our system comprises a motorized 3D ultrasound (US) transducer mounted on a robotic arm and equipped with a needle guide. It continuously registers US sweeps in real time with a pre-interventional plan based on CT or MR images and annotations. While a visual control law maintains anatomy visibility and alignment of the needle guide, a force controller is employed for acoustic coupling and tissue pressure. We validate the servoing capabilities of our method on a geometric gel phantom and real human anatomy, and the needle targeting accuracy using CT images on a lumbar spine gel phantom under neurosurgery conditions. Results Despite the varying resolution of the acquired Oliver Zettinig and Benjamin Frisch have contributed equally to this work. Yu-Mi Ryang and Nassir Navab have contributed equally to this work.B Oliver Zettinig 3D sweeps, we achieved direction-independent positioning errors of 0.35±0.19 mm and 0.61 • ±0.45 • , respectively. Our method is capable of compensating movements of around 25 mm/s and works reliably on human anatomy with errors of 1.45 ± 0.78 mm. In all four manual insertions by an expert surgeon, a needle could be successfully inserted into the facet joint, with an estimated targeting accuracy of 1.33±0.33 mm, superior to the gold standard. Conclusion The experiments demonstrated the feasibility of robotic ultrasound-based navigation and needle guidance for neurosurgical applications such as lumbar spine injections.

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“…This interaction matrix describes a simplified behavior of the system since the effect of the out-of-plane motions is neglected. Compared to the complete matrix given in (10), this one has great decoupling properties and is only dependent of the image features. In particular, the components of the estimated normal vector to the object surface are no longer involved.…”

Section: Interaction Modelingmentioning

confidence: 99%

“…To control these four DOF, the coordinates of two image points corresponding to the intersection of the forceps jaws with the image plane are used as visual features [8], [9]. More recently, Nakadate et al described in [10] an intensity-based method to track the out-of-plane translation of the carotid artery. One DOF of the robotic system is then controlled using an inter-frame block matching method to identify the artery motion.…”

Section: Introductionmentioning

confidence: 99%

Moments-Based Ultrasound Visual Servoing: From a Mono- to Multiplane Approach

et al. 2016

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This paper presents a new image-based visual servoing approach to control a robotic system equipped with an ultrasound imaging device. The presented method allows an automatic positioning of the probe with respect to an object of interest. Moments-based image features are computed from three orthogonal ultrasound images to servo in-plane and out-of-plane motions of the system. An efficient segmentation method, based on graph cut strategy, is proposed to extract the object contour in each image plane. Simulation results demonstrate that this approach improves upon techniques based on a single 2D US image in terms of probe positioning. Our method was also validated from robotic experiments performed on an ultrasound phantom with the use of a motorized 3D probe that provides the three US images.

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Out-of-plane visual servoing method for tracking the carotid artery with a robot-assisted ultrasound diagnostic system

Cited by 30 publications

References 15 publications

Confidence-driven control of an ultrasound probe: Target-specific acoustic window optimization

Confidence-driven control of an ultrasound probe: Target-specific acoustic window optimization

3D ultrasound registration-based visual servoing for neurosurgical navigation

Moments-Based Ultrasound Visual Servoing: From a Mono- to Multiplane Approach

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