Robust Augmented Reality registration method for Localization of Solid Organs’ Tumors Using CT-derived Virtual Biomechanical Model and Fluorescent Fiducials

Seong-Ho Kong 1 Nazim Haouchine 2 Renato Soares 2 Andrey S Klymchenko 3 Bohdan Andreiuk 3 Bruno Marques 4 Galyna Shabat 5 Thierry Piéchaud 6 Michele Diana 2 Stéphane Cotin 4 Jacques Marescaux 5
1 Seoul National University Hospital
2 IHU Strasbourg - L'Institut hospitalo-universitaire de Strasbourg
3 LBP - Laboratoire de Biophotonique et Pharmacologie - UMR 7213
4 MIMESIS - Computational Anatomy and Simulation for Medicine
Inria Nancy - Grand Est
5 IRCAD/EITS - Institut de Recherche Contre les Cancers de l'Appareil Digestif-European Institute of Telesurgery
6 Clinique Saint Augustin
Abstract : Accurate localization of solid organs tumors is crucial to ensure both radicality and organ function preservation. Augmented Reality (AR) is the fusion of computer-generated and real-time images. AR can be used in surgery as a navigation tool, by creating a patient-specific virtual model through 3D software manipulation of DICOM imaging (e.g. CT-scan). The virtual model can be superimposed to the real-time images to obtain the enhanced real-time localization. However, the 3D virtual model is rigid, and does not take into account inner structures’ deformations. We present a concept of automated navigation system, enabling transparency visualization of internal anatomy and tumor’s margins, while the organs undergo deformation during breathing or surgical manipulation.
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Article dans une revue
Surgical Endoscopy, Springer Verlag (Germany), 2016, 〈10.1007/s00464-016-5297-8〉
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Dernière modification le : vendredi 16 décembre 2016 - 10:55:52
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Seong-Ho Kong, Nazim Haouchine, Renato Soares, Andrey S Klymchenko, Bohdan Andreiuk, et al.. Robust Augmented Reality registration method for Localization of Solid Organs’ Tumors Using CT-derived Virtual Biomechanical Model and Fluorescent Fiducials. Surgical Endoscopy, Springer Verlag (Germany), 2016, 〈10.1007/s00464-016-5297-8〉. 〈hal-01314963v2〉

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