Surgical Motion Adaptive Robotic Technology (S.M.A.R.T): Taking the Motion out of Physiological Motion

Thakral, Anshul; Wallace, Jeffrey; Tomlin, Damian H.; Seth, Nikesh; Thakor, Nitish V.

doi:10.1007/3-540-45468-3_38

Cited by 57 publications

(37 citation statements)

References 10 publications

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“…These include the use of pre-operative imaging combined with 2D/3D registration such that the underlying structure and morphology of the soft-tissue can be provided. To cater for tissue deformation, structure from light [1] or motion sensors such as mechanically or optically based accelerometers [2,3] are used. With the increasing availabilities of stereo-laparoscope cameras, detailed 3D motion and structure recovery techniques based on stereo vision have also be proposed recently [4,5].…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Stereoscope Localization and Soft-Tissue Mapping for Minimal Invasive Surgery

Mountney

Stoyanov

Davison

et al. 2006

Lecture Notes in Computer Science

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Abstract. Minimally Invasive Surgery (MIS) has recognized benefits of reduced patient trauma and recovery time. In practice, MIS procedures present a number of challenges due to the loss of 3D vision and the narrow field-ofview provided by the camera. The restricted vision can make navigation and localization within the human body a challenging task. This paper presents a robust technique for building a repeatable long term 3D map of the scene whilst recovering the camera movement based on Simultaneous Localization and Mapping (SLAM). A sequential vision only approach is adopted which provides 6 DOF camera movement that exploits the available textured surfaces and reduces reliance on strong planar structures required for range finders. The method has been validated with a simulated data set using real MIS textures, as well as in vivo MIS video sequences. The results indicate the strength of the proposed algorithm under the complex reflectance properties of the scene, and the potential for real-time application for integrating with the existing MIS hardware.

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Section: Introductionmentioning

confidence: 99%

Simultaneous Stereoscope Localization and Soft-Tissue Mapping for Minimal Invasive Surgery

Mountney

Stoyanov

Davison

et al. 2006

Lecture Notes in Computer Science

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“…For robotic heart surgery, Ortmaier et al [92] uses a multisensor prediction scheme consisting of the patient's electrocardiogram, a respiration pressure signal, and tracking data of natural landmarks on the heart surface. Like similar approaches (Trejos et al [112], Thakral et al [110], Nakamura et al [85], and more recently by Cuvillon et al [17] and Bebek et al [8]), Ortmaier et al are aiming at an integration of automatic heart beat compensation into telemanipulator surgery systems.…”

Section: Organ Shift and Tissue Deformationmentioning

confidence: 99%

Navigation in Endoscopic Soft Tissue Surgery: Perspectives and Limitations

Baumhauer

Feuerstein

Meinzer

et al. 2008

Journal of Endourology

163

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Abstract-Despite rapid developments in the research areas medical imaging, medical image processing and robotics, the use of computer assistance in surgical routine is still limited to diagnostics, surgical planning, and interventions on mostly rigid structures. In order to establish a computer aided workflow from diagnosis to surgical treatment and follow-up, several proposals for computer assisted soft tissue interventions have been made in recent years. By means of different pre-and intraoperative information sources, like surgical plannings, intraoperative imaging, and tracking devices, surgical navigation systems aim at supporting surgeons in localizing anatomical targets, observing critical structures, and sparing healthy tissue. Current research in particular addresses the problem of organ shift and tissue deformation, and obstacles in communication between navigation system and surgeon.In this article, we review computer assisted navigation systems for soft tissue surgery. We concentrate on approaches which can be applied in endoscopic thoracic and abdominal surgery, as endoscopic surgery has special needs for image guidance due to limitations in perception. Furthermore, this article provides the reader with new trends and technologies in the area of computer assisted surgery. Finally, a balancing of key challenges and possible benefits of endoscopic navigation refines the perspectives of this increasingly important discipline of computer aided medical procedures.

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“…On one hand, the classical frequential approach filters the global motion to extract the respiration component. One can use a lowpass filter or adaptive filter [1], or also Fourier coefficient estimation [5] to suppress heart beating harmonics with equivalent results. In this study, a kaiser-FIR lowpass filter with a cut-off frequency located between the fundamental of the beating f b and the last significant harmonic of the respiration (4f r) is used to separate the 2 components.…”

Section: Validation and Comparison With Other Approachesmentioning

confidence: 99%

“…In [4], Ortmaier studies robust motion prediction of heart landmarks with ECG and respiration as additional robust landmark. In [5], Fourier coefficients of respiratory and cardiac components are estimated by a two-stage adaptive algorithm. A similar approach based on adaptive filtering to separate the two components and predict the future motion is presented in [1].…”

Section: Introductionmentioning

confidence: 99%

Toward Robotized Beating Heart TECABG: Assessment of the Heart Dynamics Using High-Speed Vision

Cuvillon

Gangloff

Mathelin

et al. 2005

Lecture Notes in Computer Science

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Abstract. Active robotic filtering is a promising solution for beating heart Totally Endoscopic Coronary Artery Bypass Grafting (TECABG). In this work, we assess the heart motion dynamics using simultaneously high speed imaging of optical markers attached to the heart, ECG signals and ventilator airflow acquisitions. Our goal is to make an assessment of the heart motion (shape, velocity, acceleration) in order to be able to make more accurate specifications for a dedicated robot that could follow this motion in real-time. Furthermore, using the 2 additional inputs (ECG, airflow), we propose a prediction algorithm of the motion that could be used with a predictive control algorithm to improve the tracking accuracy.

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Surgical Motion Adaptive Robotic Technology (S.M.A.R.T): Taking the Motion out of Physiological Motion

Cited by 57 publications

References 10 publications

Simultaneous Stereoscope Localization and Soft-Tissue Mapping for Minimal Invasive Surgery

Simultaneous Stereoscope Localization and Soft-Tissue Mapping for Minimal Invasive Surgery

Navigation in Endoscopic Soft Tissue Surgery: Perspectives and Limitations

Toward Robotized Beating Heart TECABG: Assessment of the Heart Dynamics Using High-Speed Vision

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