Intelligent control algorithms for robotic-assisted beating heart surgery

Bebek, Özkan; Çavuşoğlu, M. Cenk

doi:10.1109/tro.2007.895077

Cited by 135 publications

(174 citation statements)

References 22 publications

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“…2. During three breathing periods no compensation is applied, then at t = 15s, the predictive controller R-GPC is launched and compared with the classical control law (6). From the first period the probe follows the liver motion and the misalignment measure defined as C (s) = (s − s * ) (s − s * ) is significantly reduced with both approaches (see Fig.…”

Section: Simulation Results With a Human Livermentioning

confidence: 99%

“…In the same context of beating heart surgery, a motion prediction scheme is developed in [5] to increase the robustness of the detection and the tracking of natural landmarks on the heart surface in a laparoscopic view. More generally, Bebek et al [6] describe improvements in motion canceling by taking into account biological signals (ECG) in the predictive algorithm. Recently, a comparison between various predictive filtering methods has been proposed in [7] to predict the motion of the mitral valve annulus.…”

Section: Introductionmentioning

confidence: 99%

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Automatic Tracking of an Organ Section with an Ultrasound Probe: Compensation of Respiratory Motion

Nadeau

Krupa

Gangloff

2011

Lecture Notes in Computer Science

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Abstract. In minimally invasive surgery or needle insertion procedures, the ultrasound imaging can easily and safely be used to visualize the target to reach. However the manual stabilization of the view of this target, which undergoes the physiological motions of the patient, can be a challenge for the surgeon. In this paper, we propose to perform this stabilization with a robotic arm equipped with a 2D ultrasound probe. The six degrees of freedom of the probe are controlled by an image-based approach, where we choose as visual feedback the image intensity. The accuracy of the control law is ensured by the consideration of the periodicity of the physiological motions in a predictive controller. Tracking tasks performed on a realistic abdominal phantom validate the proposed approach and its robustness to deformation is assessed on a gelatin-made deformable phantom.

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Section: Simulation Results With a Human Livermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automatic Tracking of an Organ Section with an Ultrasound Probe: Compensation of Respiratory Motion

Nadeau

Krupa

Gangloff

2011

Lecture Notes in Computer Science

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“…High-speed cameras can be used to visualize the exterior surface of the heart [4] and ultrasound images can be used to visualize both the exterior and the interior surfaces of the heart [5]. In addition, sonomicrometry crystals can be sutured to the heart to track the position of a specific point on the heart [6]; as it is not practical to suture sonomicrometry crystals to the heart during surgery, this method is more appropriate for validation of control techniques.…”

Section: Prior Artmentioning

confidence: 99%

“…If a delay is introduced by the first element, however, the current position of the heart must be estimated. This can be accomplished with an extended Kalman filter [7] or by temporally adjusting the previous heart beat motion to match the current heart rate [6]. Depending on whether the surgical robot is directly held by the surgeon or is teleoperated from a user interface, there may be a need for additional delay compensation steps.…”

Section: Prior Artmentioning

confidence: 99%

Development of a Robotic System to Enable Beating-heart Surgery

Bowthorpe¹,

Castonguay-Siu²,

Tavakoli³

2014

JRSJ

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“…These methods [14,15] deal with the tracking of an intervention point on the heart surface without taking into account the movement of the intervention area.…”

Section: Related Workmentioning

confidence: 99%

Efficient physics-based tracking of heart surface motion for beating heart surgery robotic systems

2010

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Purpose Tracking of beating heart motion in a robotic surgery system is required for complex cardiovascular interventions. Methods A heart surface motion tracking method is developed, including a stochastic physics-based heart surface model and an efficient reconstruction algorithm. The algorithm uses the constraints provided by the model that exploits the physical characteristics of the heart. The main advantage of the model is that it is more realistic than most standard heart models. Additionally, no explicit matching between the measurements and the model is required. The application of meshless methods significantly reduces the complexity of physics-based tracking. Results Based on the stochastic physical model of the heart surface, this approach considers the motion of the intervention area and is robust to occlusions and reflections. The tracking algorithm is evaluated in simulations and experiments on an artificial heart. Providing higher accuracy than the standard model-based methods, it copes successfully with occlusions and provides high performance when all measurements are not available. Conclusions Combining the physical and stochastic description of the heart surface motion ensures physically correct and accurate prediction. Automatic initialization of the physics-based cardiac motion tracking enables system evaluation in a clinical environment.

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Intelligent control algorithms for robotic-assisted beating heart surgery

Cited by 135 publications

References 22 publications

Automatic Tracking of an Organ Section with an Ultrasound Probe: Compensation of Respiratory Motion

Automatic Tracking of an Organ Section with an Ultrasound Probe: Compensation of Respiratory Motion

Development of a Robotic System to Enable Beating-heart Surgery

Efficient physics-based tracking of heart surface motion for beating heart surgery robotic systems

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