Russell C. Jackson

Needle path planning for autonomous robotic surgical suturing

This paper develops a path plan for suture needles used with solid tissue volumes in endoscopic surgery. The path trajectory is based on the best practices that are used by surgeons. The path attempts to minimize the interaction forces between the tissue and the needle. Using surgical guides as a basis, two different techniques for driving a suture needle are developed. The two techniques are compared in hardware experiments by robotically driving the suture needle using both of the motion plans.

Modeling of needle-tissue interaction forces during surgical suturing

This paper presents a model of needle tissue interaction forces that a rigid suture needle experiences during surgical suturing. The needle-tissue interaction forces are modeled as the sum of lumped parameters. The model has three main components; friction, tissue compression, and cutting forces. The tissue compression force uses the area that the needle sweeps out during a suture to estimate both the force magnitude and force direction. The area that the needle sweeps out is a direct result of driving the needle in a way that does not follow the natural curve of the needle. The friction force is approximated as a static friction force along the shaft of the needle. The cutting force acts only on the needle tip. The resulting force and torque model is experimentally validated using a tissue phantom. These results indicate that the proposed lumped parameter model is capable of accurately modeling the forces experienced during a suture.

Estimation of soft tissue mechanical parameters from robotic manipulation data

Robotic motion planning algorithms used for task automation in robotic surgical systems rely on availability of accurate models of target soft tissues deformation. Relying on generic tissue parameters in constructing the tissue deformation models is problematic because biological tissues are known to have very large (inter- and intra-subject) variability. A priori mechanical characterization (e.g., uniaxial bench test) of the target tissues before a surgical procedure is also not usually practical. In this paper, a method for estimating mechanical parameters of soft tissue from sensory data collected during robotic surgical manipulation is presented. The method uses force data collected from a multiaxial force sensor mounted on the robotic manipulator, and tissue deformation data collected from a stereo camera system. The tissue parameters are then estimated using an inverse finite element method. The effects of measurement and modeling uncertainties on the proposed method are analyzed in simulation. The results of experimental evaluation of the method are also presented.

A novel vision guided knot-tying method for autonomous robotic surgery

This paper presents a vision guided automatic knot-tying method for Robotic Assisted Minimally Invasive Surgery. By utilizing 3D position reconstruction of selection points on images from calibrated stereo cameras and coordinating two robot motions for proper suture handling, we successfully realize an automatic knot-tying procedure. Our experimental results show that autonomous knot-tying has the potential to be faster than human performance, thus supporting supervisory control.

Automatic initialization and dynamic tracking of surgical suture threads

In order to realize many of the potential benefits associated with robotically assisted minimally invasive surgery, the robot must be more than a remote controlled device. Currently using a surgical robot can be challenging, fatiguing, and time consuming. Teaching the robot to actively assist surgical tasks, such as suturing, has the potential to vastly improve both patient outlook and the surgeons efficiency. One obstacle to completing surgical sutures autonomously is the difficulty in tracking surgical suture threads. This paper proposes an algorithm which uses a Non-Uniform Rational B-Spline (NURBS) curve to model a suture thread. The NURBS model is initialized from a single selected point located on the thread. The NURBS curve is optimized by minimizing the image match energy between the projected stereo NURBS image and the segmented thread image. The algorithm is able to accurately track a suture thread as it translates, deforms, and changes length in real-time.

Catadioptric stereo tracking for three dimensional shape measurement of MRI guided catheters

The recent introduction of Magnetic Resonance Imaging (MRI)-actuated steerable catheters lays the ground work for increasing the efficacy of cardiac catheter procedures. The MRI, while capable of imaging the catheter for tracking and control, does not fulfill all of the needs required to identify and develop a complete catheter model. Specifially, the frequency response of the catheter must be identified to ensure stable control of the catheter system. This requires a higher frequency imaging than the MRI can achieve. This work uses a catadioptric stereo camera system consisting of a mirror and a single camera in order to track a MRI actuated catheter inside a MRI machine. The catadioptric system works in parallel to the MRI and is capable of recording the catheter at 60 fps for post processing. The accuracy of the catadioptric system is verified in imaging conditions that would be found inside the MRI. The stereo camera is then used to track a catheter as it is actuated inside the MRI.

Needle-tissue interaction force state estimation for robotic surgical suturing

Robotically Assisted Minimally Invasive Surgery (RAMIS) offers many advantages over manual surgical techniques. Most of the limitations of RAMIS stem from its nonintuitive user interface and costs. One way to mitigate some of the limitations is to automate surgical subtasks (e.g. suturing) such that they are performed faster while allowing the surgeon to plan the next step of the procedure. One component of successful suture automation is minimizing the internal tissue deformation forces generated by driving a needle through tissue. Minimizing the internal tissue forces requires segmenting the tissue deformation forces from other components of the needle tissue interaction (e.g. friction force). This paper proposes an Unscented Kalman Filter which can successfully model the force components, in particular the internal deformation force, generated by a needle as it is driven through a sample of tissue.

Real-Time Visual Tracking of Dynamic Surgical Suture Threads

In order to realize many of the potential benefits associated with robotically assisted minimally invasive surgery, the robot must be more than a remote controlled device. Currently, using a surgical robot can be challenging, fatiguing, and time-consuming. Teaching the robot to actively assist surgical tasks, such as suturing, has the potential to vastly improve both the patient’s outlook and the surgeon’s efficiency. One obstacle to completing surgical sutures autonomously is the difficulty in tracking surgical suture threads. This paper presents novel stereo image processing algorithms for the detection, initialization, and tracking of a surgical suture thread. A nonuniform rational B-spline (NURBS) curve is used to model a thin, deformable, and dynamic length thread. The NURBS model is initialized and grown from a single selected point located on the thread. The NURBS curve is optimized by minimizing the image matching energy between the projected stereo NURBS image and the segmented thread image. The algorithms are evaluated using suture threads, a calibrated test pattern, and a simulated thread image. In addition, the accuracies of the algorithms presented are validated as they track a suture thread undergoing translation, deformation, and apparent length changes. All of the tracking is in real time. Note to Practitioners—The problem of tracking a surgical suture thread was addressed in this paper. Since the suture thread is highly deformable, any tracking algorithm must be robust to intersections, occlusions, knot tying, and length changes. The detection algorithm introduced in this paper is capable of distinguishing different threads when they intersect. The tracking algorithm presented here demonstrates that it is possible, using polynomial curves, to track a suture thread as it deforms, becomes occluded, changes length, and even ties a knot in real time. The detection algorithm can enhance directional thin features, while the polynomial curve modeling can track any string-like structure. Further integration of the polynomial curve with a feed-forward thread model could improve the stability and robustness of the thread tracking.

Experimental validation of the pseudo-rigid-body model of the MRI-actuated catheter

An MRI-actuated catheter is a novel robotic catheter system that utilizes the MRI for both remote steering and visualization for catheter ablation of atrial fibrillation. Planning and control of the catheter requires a sufficiently fast yet accurate model of the catheter. The pseudo-rigid-body (PRB) model offers a reasonable trade-off between speed and accuracy by approximating the continuum catheter as rigid links connected by flexible joints, thus reducing the infinite degrees of freedom of the continuum mechanism to a finite one. In this paper, a PRB model of the MRI-actuated catheter is validated experimentally by comparing the deflections of the PRB model with the deflections of the catheter prototype.

Iterative Jacobian-Based Inverse Kinematics and Open-Loop Control of an MRI-Guided Magnetically Actuated Steerable Catheter System

This paper presents an iterative Jacobian-based inverse kinematics method for a magnetic resonance imaging (MRI) guided magnetically actuated steerable intravascular catheter system. The catheter is directly actuated by magnetic torques generated on a set of current-carrying microcoils embedded on the catheter tip by the magnetic field of the MRI scanner. The Jacobian matrix relating changes of the currents through the coils to changes of the tip position is derived using a three-dimensional kinematic model of the catheter deflection. The inverse kinematics is numerically computed by iteratively applying the inverse of the Jacobian matrix. The damped least square method is implemented to avoid numerical instability issues that exist during the computation of the inverse of the Jacobian matrix. The performance of the proposed inverse kinematics approach is validated using a prototype of the robotic catheter by comparing the actual trajectories of the catheter tip obtained via open-loop control with the desired trajectories. The results of reproducibility and accuracy evaluations demonstrate that the proposed Jacobian-based inverse kinematics method can be used to actuate the catheter in an open loop to successfully perform complex ablation trajectories required in atrial fibrillation ablation procedures. This study paves the way for effective and accurate closed-loop control of the robotic catheter with real-time feedback from MRI guidance in subsequent research.