Allan, M;
Ourselin, S;
Hawkes, DJ;
Kelly, JD;
Stoyanov, D;
(2018)
3D Pose Estimation of Articulated Instruments in Robotic Minimally Invasive Surgery.
IEEE Transactions on Medical Imaging
, 37
(5)
10.1109/TMI.2018.2794439.
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Abstract
Estimating the 3D pose of instruments is an important part of robotic minimally invasive surgery (RMIS) for automation of basic procedures as well as providing safety features such as virtual fixtures. Image based methods of 3D pose estimation provide a non-invasive low cost solution compared with methods that incorporate external tracking systems. In this work we extend our recent work in estimating rigid 3D pose with silhouette and optical flow based features to incorporate the articulated degrees of freedom (DOF) of robotic instruments within a gradient based optimization framework. Validation of the technique is provided with a calibrated ex-vivo study from the DVRK robotic system where we perform quantitative analysis on the errors each DOF of our tracker. Additionally we perform several detailed comparisons with recently published techniques that combine visual methods with kinematic data acquired from the joint encoders. Our experiments demonstrate that our method is competitively accurate while relying solely on image data.
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