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.