3D Ultrasound-Guided Motion Compensation System for Beating Heart Mitral Valve Repair

Yuen, Shelten G.; Kesner, Samuel B.; Vasilyev, Nikolay V.; Nido, Pedro J. del; Howe, Robert D.

doi:10.1007/978-3-540-85988-8_85

Cited by 46 publications

(50 citation statements)

References 11 publications

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“…Yuen et al (2008) presented a real-time motion compensation system for ultrasound volumes, such that mitral valve repair can be performed while the heart is beating. By utilizing the fact that the motion of some intra cardiac structures is largely constrained to translation along one axis, the motion could be estimated at 28 Hz.…”

Section: Image Registrationmentioning

confidence: 99%

Medical image processing on the GPU – Past, present and future

Eklund

Dufort

Forsberg

et al. 2013

Medical Image Analysis

351

198

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Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, histogram estimation and distance transforms), the most commonly used algorithms in medical imaging (image registration, image segmentation and image denoising) and algorithms that are specific to individual modalities (CT, PET, SPECT, MRI, fMRI, DTI, ultrasound, optical imaging and microscopy). The review ends by highlighting some future possibilities and challenges.

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Section: Image Registrationmentioning

confidence: 99%

Medical image processing on the GPU – Past, present and future

Eklund

Dufort

Forsberg

et al. 2013

Medical Image Analysis

351

198

View full text Add to dashboard Cite

show abstract

“…For example, in [6], while the proposed boundary segmentation method achieved very high accuracy, the computational time was 10 seconds per slice. In contrast, Yuen et al [7] achieved real-time performance in Ultrasound images with an extended Kalman filter tracker.…”

Section: Introductionmentioning

confidence: 97%

Collaborative Tracking for MRI-Guided Robotic Intervention on the Beating Heart

Zhou

Yeniaras

Tsiamyrtzis

et al. 2010

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010

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Abstract. Magnetic Resonance Imaging (MRI)-guided robotic interventions for aortic valve repair promise to dramatically reduce time and cost of operations when compared to endoscopically guided (EG) procedures. A challenging issue is real-time and robust tracking of anatomical landmark points. The interventional tool should be constantly adjusted via a closed feedback control loop to avoid harming these points while valve repair is taking place in the beating heart. A Bayesian network of particle filter trackers proves capable to produce real-time, yet robust behavior. The algorithm is extremely flexible and general -more sophisticated behaviors can be produced by simply increasing the cardinality of the tracking network. Experimental results on 16 MRI cine sequences highlight the promise of the method.

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“…However, these systems do not provide sufficient speeds to compensate for the motion of the heart. Fast motion compensation is required for many beating heart procedures to enable dexterous interaction and prevent the catheter from colliding with internal cardiac structures [5].…”

Section: Introductionmentioning

confidence: 99%

“…In previous work, we developed robotic devices that compensate for the motion of internal heart structures with a handheld robotic instrument inserted through incisions in the heart wall [5], [9]- [11]. This work shows that single degree of freedom (DOF) servoing is sufficient to accurately track the motion of certain cardiac structures, including the human mitral valve annulus [9], [11].…”

Section: Introductionmentioning

confidence: 99%

Ultrasound Servoing of Catheters for Beating Heart Valve Repair

Kesner

Yuen

Howe

2010

Information Processing in Computer-Assisted Interventions

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Abstract. Robotic cardiac catheters have the potential to revolutionize heart surgery by extending minimally invasive techniques to complex surgical repairs inside the heart. However, catheter technologies are currently unable to track fast tissue motion, which is required to perform delicate procedures inside a beating heart. This paper presents an actuated catheter tool that compensates for the motion of heart structures like the mitral valve apparatus by servoing a catheter guidewire inside a flexible sheath. We examine design and operation parameters and establish that friction and backlash limit the tracking performance of the catheter system. Based on the results of these experiments, we implement compensation methods to improve trajectory tracking. The catheter system is then integrated with an ultrasound-based visual servoing system to enable fast tissue tracking. In vivo tests show RMS tracking errors of 0.77 mm for following the porcine mitral valve annulus trajectory. The results demonstrate that an ultrasound-guided robotic catheter system can accurately track the fast motion of the mitral valve.

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3D Ultrasound-Guided Motion Compensation System for Beating Heart Mitral Valve Repair

Cited by 46 publications

References 11 publications

Medical image processing on the GPU – Past, present and future

Medical image processing on the GPU – Past, present and future

Collaborative Tracking for MRI-Guided Robotic Intervention on the Beating Heart

Ultrasound Servoing of Catheters for Beating Heart Valve Repair

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