Date 02.2014 — now
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Needle insertion is a key procedure in minimally invasive surgery including percutaneous (through the skin) therapies.
It is seemingly very simple: a surgeon aims the needle at the anatomical target (with the target position determined from high-quality medical image acquired before surgery).
During the insertion, the tissue deforms and the target moves due to the interactions between the needle and tissue.
Although, surgeon’s hands can be replaced with a robotic manipulator to ensure that the planned needle trajectory is precisely followed, neither the robot nor the surgeon can predict the deforming tissue and moving target.
Consequently, the risk of missing the target is substantial.
The goal of this project is to use the finite element (FE) bio-mechanical models to predict the tissue deformations and surgical target movement, then to integrate this prediction with surgical robot control, in order to improve the insertion accuracy and to decrease the risk of adverse effects.
Silhouette-based Pose Estimation for Deformable Organs Application to Surgical Augmented Reality Yinoussa Adagolodjo, Raffaella Trivisonne, Nazim Haouchine, Stéphane Cotin, Hadrien CourtecuisseIROS 2017 – IEEE/RSJ International Conference on Intelligent Robots and Systems, Sep 2017, Vancouver, Canada. 2017
Inverse real-time Finite Element simulation for robotic control of flexible needle insertion in deformable tissues inoussa Adagolodjo, Laurent Goffin, Michel De Mathelin, Hadrien CourtecuisseIEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016) , Oct 2016, Daejeon, South Korea. 〈http://www.iros2016.org/〉
Haptic Rendering of Hyperelastic Models with Friction Hadrien Courtecuisse, Yinoussa Adagolodjo, Hervé Delingette, Christian Duriez2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sep 2015, Hamburg, Germany. IEEE, pp.591-596, 2015, 〈10.1109/IROS.2015.7353432〉