Model-based robust pose estimation for a multi-segment, programmable bevel-tip steerable needle

Bevel-tip steerable needles for percutaneous intervention are prone to torsion determined by the interaction forces with the human tissue. If disregarded, torsion can affect the insertion accuracy inducing a change in the needle tip orientation, which is generally undetectable by tracking devices be...

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Bibliographic Details
Published in:IEEE robotics and automation letters 2020-10, Vol.5 (4), p.1-1
Main Authors: Favaro, Alberto, Secoli, Riccardo, Rodriguez y Baena, Ferdinando, De Momi, Elena
Format: Article
Language:English
Subjects:
Bevels
Biologically-Inspired Robots
Computer simulation
Diameters
Extended Kalman filter
Gelatin
Human tissues
Medical Robots and Systems
Orientation
Percutaneous treatment
Pose estimation
Position measurement
Steerable Catheters/Needles
Steering
Surgical Robotics
Tracking devices
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Summary:Bevel-tip steerable needles for percutaneous intervention are prone to torsion determined by the interaction forces with the human tissue. If disregarded, torsion can affect the insertion accuracy inducing a change in the needle tip orientation, which is generally undetectable by tracking devices because of the small diameter of the needle. This paper presents a method for estimating the tip pose (i.e. position and orientation) of a programmable bevel-tip needle using a 2-D kinematic based Extended Kalman Filter (EKF), where the tip position of the two steering segments is used as input measurement. Simulation trials and experiments in phantom-brain gelatin were performed to prove the performance of the method and mimic real case scenarios. The solution presented shows state-of-the-art performance in needle pose estimation with a bounded positional error of
ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2020.3018406