Multi-rate unscented Kalman filtering for pose and curvature estimation in 3D ultrasound-guided needle steering. (November 2018)

• Record Type: Journal Article
• Authors: Lapouge, G.; Troccaz, J.; Poignet, P.
• Is Part Of: Control engineering practice. Volume 80(2018)
• Page Start: 116
• Page End: 124
• Publication Date: 2018-11
• Subjects: Needle steering -- Surgical robotics -- Multi-rate unscented Kalman filter -- 3D ultrasound imaging; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2018.08.014
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: This paper presents a new method for estimating the needle pose and curvature in the context of robotically steered needles. The needle tip trajectory is represented by a modified unicycle kinematic model. A multi-rate unscented Kalman filter is proposed for the first time in needle steering to fuse asynchronous data coming from 3D B-mode ultrasound images, robot sensors and pre-operative elastography measurements. To demonstrate it, 51 unconstrained 3D insertions have been made in various media. The instantaneous localisation error is smaller than 0.6 mm and the prediction of the final tip position is smaller than 2 mm based on the observation of the first 2 cm of 8 cm deep insertions. Highlights: This paper presents an observer for 3D needle steering and 3D ultrasound imaging. This observer enables multi-sensor, asynchronous measurements. Changes in medium elasticity are taken into account for online curvature estimation. The needle tip Cartesian position is precisely estimated in noisy ultrasound images. The tip final position is precisely estimated after observing 2 cm of 8 cm insertions.