Search

We present a novel algorithm for needle tracking in ultrasound-guided needle insertion. Most previous research assumes that in ultrasound images the needle is a straight and bright line, but needles can bend due to the interaction with heterogeneous tissue. We utilize a novel weighted RANSAC curve fitting method combined with probabilistic Hough transform to track the curved needle robustly, and the algorithm can additionally utilize external tracking information, such as robotic kinematics, to further improve the tracking accuracy. We compared against classical tracking algorithms and a U-Net model, testing over different needle curvature and tissues. Our proposed algorithm achieves higher accuracy in tip location, shaft fitting, and tip angle. In-vivo porcine experiments with naturally bending short needles also show our method better tracked the tip location.