Image Navigation in Minimally Invasive Surgery

Pyciński, Bartłomiej; Juszczyk, Jan; Bozek, P; Ciekalski, Jacek; Dzielicki, Józef; Piętka, Ewa

doi:10.1007/978-3-319-06596-0_3

Cited by 8 publications

(5 citation statements)

References 20 publications

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“…Calibrated ToF-camera is a device which could be potentially deployed at the stage of positioning an object in the navigation system space. The results from Tables 3 and 4 confirm, that the worst alignment between optical tracker and ToF camera (1.8 cm, p m = 10%) is at the level of acceptance even in some medical fields [ 11 ]. Moreover, our experiments showed that if the number of rejected points is decreased to 3%, the misalignment is still acceptable.…”

Section: Discussionmentioning

confidence: 65%

“…Several modalities might be implemented here, e.g. ultrasonography (USG) [ 3 , 4 ], endoscopy [ 5 , 6 ], bronchoscopy [ 7 ], visual navigation systems [ 8 – 11 ], or time-of-flight (ToF) cameras [ 12 , 13 ]. The issues of equipment synchronization, mutual spatial data correspondence, and finally the registration algorithms are covered by the intra-operative computer-aided surgery (CAS) systems designed for specific purposes [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

“…the CT, plays a big role in treatment planning. The optical navigation system stands for a reliable positioning tool [ 11 ]. Finally, the noninvasive ToF depth measurement offers a number of points as a surface representation, matchable to the CT-segmented structures.…”

Section: Introductionmentioning

confidence: 99%

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Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration

et al. 2016

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PurposeA growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed.MethodsWe present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm.ResultsThe experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera.ConclusionThe obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

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Section: Discussionmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 99%

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Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration

et al. 2016

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“…The success of cardiac interventions over the last three decades has significantly reduce the mortality and morbidity of coronary, valvular, and various congenital diseases [10,11] . However, expansion of MIS to more complex surgeries demand further development of new technologies, including robotic surgical systems [12] , navigation [13] , guidance [14] , and visualizations [15] , dexterity enhancement [16] , and 3D printing technology [17] .…”

Section: Introductionmentioning

confidence: 99%

Deep learning-driven catheter tracking from bi-plane X-ray fluoroscopy of 3D printed heart phantoms

Torabinia¹,

Caprio²,

Jang³

et al. 2021

MIS

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Minimally invasive surgery (MIS) has changed not only the performance of specific operations but also the more effective strategic approach to all surgeries. Expansion of MIS to more complex surgeries demands further development of new technologies, including robotic surgical systems, navigation, guidance, visualizations, dexterity enhancement, and 3D printing technology. In the cardiovascular domain, 3D printed modeling can play a crucial role in providing improved visualization of the anatomical details and guide precision operations as well as functional evaluation of various congenital and congestive heart conditions. In this work, we propose a novel deep learning-driven tracking method for providing quantitative 3D tracking of mock cardiac interventions on customdesigned 3D printed heart phantoms. In this study, the position of the tip of a catheter is tracked from bi-plane fluoroscopic images. The continuous positioning of the catheter relative to the 3D printed model was co-registered in a single coordinate system using external fiducial markers embedded into the model. Our proposed method has the potential to provide quantitative analysis for training exercises of percutaneous procedures guided by bi-plane fluoroscopy.

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“…Espiau et al [17] described another method for vision-based control in robotics, in which the proposed framework incorporated the visual system into the control loop to permit interactions between the robot and its surroundings. Putzer et al [18] and Pycinski et al [19] proposed the use of time-of-flight camera for navigating robots in a computer-aid surgery.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Surgical Suture Looping Through Trajectory Planning for Wound Suturing

Chu

Huang

et al. 2019

IEEE Trans. Automat. Sci. Eng.

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Robot-assisted surgery (RAS) has revolutionized the field of surgery over the past few decades. Despite many successes, achieving full automation in these surgeries remains a challenging task. In this paper, a dynamic approach is proposed to automate knot tying with an in-house robot vision system. Through efficient path planning and coordination between two grippers, the workspace required for constructing the suture loop can be reduced while issues such as suture slippage and collisions between instruments can be eliminated. Visual images were employed to monitor the two grippers in real-time and their positions were evaluated using transformation matrices obtained experimentally. A Linear Quadratic (LQ) control scheme was applied to optimize the tracking performance of the two grippers.From the experiments, this visual evaluation method can achieve a position accuracy of 1 mm in the workspace. The proposed algorithm was evaluated and automatic suture looping operation was successfully performed in all six trials. Different parameters in the control scheme were also examined by introducing external impulse disturbances during the knot tying process. This proposed knot-tying approach demonstrates a simple and efficient way to construct a suture knot in a minimal workspace. Note to Practitioners -A surgical operation usually takes several hours to complete, which is a test of surgeon's endurance. To better assist surgeons, several repetitive surgical tasks can be performed automatically with a robotic system. This paper presents a new method for robot-assisted surgical knot tying in a confined environment. Through simultaneous manipulation and trajectory planning of the two surgical grippers, suture loops were constructed while keeping the suture in tension. Images were employed to guide the gripers in completing the knot tying process with high precision. Experiments were conducted to demonstrate the automated suture looping operation with the system and the proposed method. The robustness of the method was also examined by introducing impulse disturbances and occlusions during the experiments. This proposed method does not require complicated hardware setup, allowing easy implementations on various surgical systems.

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Image Navigation in Minimally Invasive Surgery

Cited by 8 publications

References 20 publications

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration

Deep learning-driven catheter tracking from bi-plane X-ray fluoroscopy of 3D printed heart phantoms

Vision-Based Surgical Suture Looping Through Trajectory Planning for Wound Suturing

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