Towards an Accurate Tracking of Liver Tumors for Augmented Reality in Robotic Assisted Surgery

Nazim Haouchine 1 Jérémie Dequidt 1, 2 Igor Peterlik 3 Erwan Kerrien 4 Marie-Odile Berger 5 Stéphane Cotin 1, 6
1 SHACRA - Simulation in Healthcare using Computer Research Advances
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe, Inria Nancy - Grand Est
2 Université de Lille, Sciences et Technologies
3 IHU Strasbourg - L'Institut hospitalo-universitaire de Strasbourg
4 MAGRIT - Visual Augmentation of Complex Environments
Inria Nancy - Grand Est, LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
5 MAGRIT - Visual Augmentation of Complex Environments
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
6 LIFL - Laboratoire d'Informatique Fondamentale de Lille
Abstract : This article introduces a method for tracking the internal structures of the liver during robot-assisted procedures. Vascular network, tumors and cut planes, computed from pre-operative data, can be overlaid onto the laparoscopic view for image-guidance, even in the case of large motion or deformation of the organ. Compared to current methods, our method is able to precisely propagate surface motion to the internal structures. This is made possible by relying on a fast yet accurate biomechanical model of the liver combined with a robust visual tracking approach designed to properly constrain the model. Augmentation results are demonstrated on in-vivo sequences of a human liver during robotic surgery, while quantitative validation is performed on an ex-vivo porcine liver experimentation. Validation results show that our approach gives an accurate surface registration with an error of less than 6mm on the position of the tumor.
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Submitted on : Tuesday, June 10, 2014 - 11:21:25 AM
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  • HAL Id : hal-01003262, version 1

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Nazim Haouchine, Jérémie Dequidt, Igor Peterlik, Erwan Kerrien, Marie-Odile Berger, et al.. Towards an Accurate Tracking of Liver Tumors for Augmented Reality in Robotic Assisted Surgery. International Conference on Robotics and Automation (ICRA), Jun 2014, Hong Kong, China. ⟨hal-01003262⟩

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