Multi-rate unscented Kalman filtering for pose and curvature estimation in 3D ultrasound-guided needle steering

Guillaume Lapouge 1, 2 Jocelyne Troccaz 2 Philippe Poignet 1
1 DEXTER - Conception et commande de robots pour la manipulation
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 TIMC-IMAG-GMCAO - Gestes Medico-chirurgicaux Assistés par Ordinateur
TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525
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.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01866088
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Submitted on : Tuesday, September 4, 2018 - 11:01:17 AM
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Guillaume Lapouge, Jocelyne Troccaz, Philippe Poignet. Multi-rate unscented Kalman filtering for pose and curvature estimation in 3D ultrasound-guided needle steering. Control Engineering Practice, Elsevier, 2018, 80, pp.116-124. ⟨10.1016/j.conengprac.2018.08.014⟩. ⟨lirmm-01866088⟩

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