Titre :

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

Auteur(s) :

Haouchine, Nazim [Auteur]
Simulation in Healthcare using Computer Research Advances [SHACRA]
Dequidt, Jeremie [Auteur]
Université de Lille, Sciences et Technologies
Simulation in Healthcare using Computer Research Advances [SHACRA]
Peterlik, Igor [Auteur]
L'Institut hospitalo-universitaire de Strasbourg [IHU Strasbourg]
Kerrien, Erwan [Auteur]
Visual Augmentation of Complex Environments [MAGRIT]
Berger, Marie-Odile [Auteur]
Visual Augmentation of Complex Environments [MAGRIT]
Cotin, Stéphane [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Simulation in Healthcare using Computer Research Advances [SHACRA]

Titre de la manifestation scientifique :

International Conference on Robotics and Automation (ICRA)

Ville :

Hong Kong

Pays :

Chine

Date de début de la manifestation scientifique :

2014-06-02

Date de publication :

2014-06-02

Discipline(s) HAL :

Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Synthèse d'image et réalité virtuelle [cs.GR]
Informatique [cs]/Modélisation et simulation

Résumé en anglais : [en]

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 ...
Lire la suite >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.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL