Real-Time Visual Tracking of Dynamic Surgical Suture Threads

Shape Estimation for Elongated Deformable Object using B-spline Chained Multiple Random Matrices Model

In this paper, a B-spline chained multiple random matrix models (RMMs) representation is proposed to model geometric characteristics of an elongated deformable object. The hyper degrees of freedom structure of the elongated deformable object make its shape estimation challenging. Based on the likelihood function of the proposed B-spline chained multiple RMMs, an expectation-maximization (EM) method is derived to estimate the shape of the elongated deformable object. A split and merge method based on the Euclidean minimum spanning tree (EMST) is proposed to provide initialization for the EM algorithm. The proposed algorithm is evaluated for the shape estimation of the elongated deformable objects in scenarios, such as the static rope with various configurations (including configurations with intersection), the continuous manipulation of a rope and a plastic tube, and the assembly of two plastic tubes. The execution time is computed and the accuracy of the shape estimation results is evaluated based on the comparisons between the estimated width values and its ground-truth, and the intersection over union (IoU) metric.

Vaginal Cuff Closure With Dual-Arm Robot and Near-Infrared Fluorescent Sutures

This paper presents a dual-arm suturing robot. We extend the Smart Tissue Autonomous Robot (STAR) with a second robot manipulator, whose purpose is to manage loose suture thread, a task that was previously executed by a human assistant. We also introduce novel near-infrared fluorescent (NIRF) sutures that are automatically segmented and delimit the boundaries of the suturing task. During ex-vivo experiments of porcine models, our results demonstrate that this new system is capable of outperforming human surgeons in all but one metric for the task of vaginal cuff closure (porcine model) and is more consistent in every aspect of the task. We also present results to demonstrate that the system can perform a vaginal cuff closure during an in-vivo experiment (porcine model).

Optimization-Based Constrained Trajectory Generation for Robot-Assisted Stitching in Endonasal Surgery

The reduced workspace in endonasal endoscopic surgery (EES) hinders the execution of complex surgical tasks such as suturing. Typically, surgeons need to manipulate non-dexterous long surgical instruments with an endoscopic view that makes it difficult to estimate the distances and angles required for precise suturing motion. Recently, robot-assisted surgical systems have been used in laparoscopic surgery with promising results. Although robotic systems can provide enhanced dexterity, robot-assisted suturing is still highly challenging. In this paper, we propose a robot-assisted stitching method based on an online optimization-based trajectory generation for curved needle stitching and a constrained motion planning framework to ensure safe surgical instrument motion. The needle trajectory is generated online by using a sequential convex optimization algorithm subject to stitching kinematic constraints. The constrained motion planner is designed to reduce surrounding damages to the nasal cavity by setting a remote center of motion over the nostril. A dual concurrent inverse kinematics (IK) solver is proposed to achieve convergence of the solution and optimal time execution, in which two constrained IK methods are performed simultaneously; a task-priority based IK and a nonlinear optimization-based IK. We evaluate the performance of the proposed method in a stitching experiment with our surgical robotic system in a robot-assisted mode and an autonomous mode in comparison to the use of a conventional surgical tool. Our results demonstrate a noticeable improvement in the stitching success ratio in the robot-assisted mode and the shortest completion time for the autonomous mode. In addition, the force interaction with the tissue was highly reduced when using the robotic system.

A study on autonomous suturing task assignment in robot-assisted minimally invasive surgery

BACKGROUND

Sutures are a set of standard actions which are accomplished by multi-instruments, researchers studied the robot autonomy of suturing, which was based on movement planning completed by a single instrument, but did not consider the assignment of suturing tasks to instruments.

METHOD

A method was proposed for the autonomous suturing task assignment to instruments, which built a comprehensive evaluation index under some constraint conditions to determine the optimal scheme of the suturing task assignment to instruments.

RESULTS

An experiment of duodenal ulcer repair with a suturing operation was conducted under the guidance of a surgeon, and the results showed that the optimal scheme of the suturing task assignment was obtained by using the proposed method.

CONCLUSIONS

The proposed method can be used for autonomous suturing task assignment, which is beneficial for improving the intelligence of robot operation.

Camera-Robot Calibration for the da Vinci® Robotic Surgery System

The development of autonomous or semi-autonomous surgical robots stands to improve the performance of existing teleoperated equipment, but requires fine hand-eye calibration between the free-moving endoscopic camera and patient-side manipulator arms (PSMs). A novel method of solving this problem for the da Vinci® robotic surgical system and kinematically similar systems is presented. First, a series of image-processing and optical-tracking operations are performed to compute the coordinate transformation between the endoscopic camera view frame and an optical-tracking marker permanently affixed to the camera body. Then, the kinematic properties of the PSM are exploited to compute the coordinate transformation between the kinematic base frame of the PSM and an optical marker permanently affixed thereto. Using these transformations, it is then possible to compute the spatial relationship between the PSM and the endoscopic camera using only one tracker snapshot of the two markers. The effectiveness of this calibration is demonstrated by successfully guiding the PSM end effector to points of interest identified through the camera. Additional tests on a surgical task, namely grasping a surgical needle, are also performed to validate the proposed method. The resulting visually-guided robot positioning accuracy is better than the earlier hand-eye calibration results reported in the literature for the da Vinci® system, while supporting intraoperative update of the calibration and requiring only devices that are already commonly used in the surgical environment.

Supervised Autonomous Electrosurgery via Biocompatible Near-Infrared Tissue Tracking Techniques

Autonomous robotic surgery systems aim to improve patient outcomes by leveraging the repeatability and consistency of automation and also reducing human induced errors. However, intraoperative autonomous soft tissue tracking and robot control still remains a challenge due to the lack of structure, and high deformability of such tissues. In this paper, we take advantage of biocompatible Near-Infrared (NIR) marking methods and develop a supervised autonomous 3D path planning, filtering, and control strategy for our Smart Tissue Autonomous Robot (STAR) to enable precise and consistent incisions on complex 3D soft tissues. Our experimental results on cadaver porcine tongue samples indicate that the proposed strategy reduces surface incision error and depth incision error by 40.03% and 51.5%, respectively, compared to a teleoperation strategy via da Vinci. Furthermore, compared to an autonomous path planning method with linear interpolation between the NIR markers, the proposed strategy reduces the incision depth error by 48.58% by taking advantage of 3D tissue surface information.

Autonomous Laparoscopic Robotic Suturing with a Novel Actuated Suturing Tool and 3D Endoscope

Compared to open surgical techniques, laparoscopic surgical methods aim to reduce the collateral tissue damage and hence decrease the patient recovery time. However, constraints imposed by the laparoscopic surgery, i.e. the operation of surgical tools in limited spaces, turn simple surgical tasks such as suturing into time-consuming and inconsistent tasks for surgeons. In this paper, we develop an autonomous laparoscopic robotic suturing system. More specific, we expand our smart tissue anastomosis robot (STAR) by developing i) a new 3D imaging endoscope, ii) a novel actuated laparoscopic suturing tool, and iii) a suture planning strategy for the autonomous suturing. We experimentally test the accuracy and consistency of our developed system and compare it to sutures performed manually by surgeons. Our test results on suture pads indicate that STAR can reach 2.9 times better consistency in suture spacing compared to manual method and also eliminate suture repositioning and adjustments. Moreover, the consistency of suture bite sizes obtained by STAR matches with those obtained by manual suturing.

Current surgical practices of robotic-assisted tissue repair and reconstruction

This paper systematically reviewed and analyzed the recent publications of robotic-assisted surgeries in the field of tissue repair and reconstruction. Surgical robots can elevate skin flap more accurately and shorten the time of tissue harvest. In addition, robotic-assisted surgery has the advantage of minimal tissue trauma and thus forms minimal scar. The utilization of surgical robots reduces the occurrence of complications after oral radical tumor resection while achieving cosmetic sutures. Robotic-assisted radical mastectomy could radically remove invasive breast cancer lesions and achieve breast reconstruction in the first stage through the small incisions in the operation areas. Surgical robots enable precise microvascular anastomosis and reduce tissue edema in the surgical field. Robotic-assisted technology can help appropriately locate the target tissues at different angles during sinus and skull base surgeries and accurately place tissues during urethroplasty. The robotic-assisted technology provides a new platform for surgical innovation in the field of tissue repair and reconstruction. However, the uncertainty in the survival rate after tumor radical surgery, the increase of operating time, and the high costs are barriers for its clinical application in tissue repair and reconstructive surgery. Nevertheless, robotic-assisted technology has already demonstrated an impact on the field of tissue repair and reconstruction in a meaningful way.