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F. Lalys, L. Riffaud, D. Bouget, and P. Jannin, A Framework for the Recognition of High-Level Surgical Tasks From Video Images for Cataract Surgeries, IEEE Transactions on Biomedical Engineering, vol.59, issue.4, pp.966-976
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M. Mehri, F. Lalys, C. Maumet, C. Haegelen, and P. Jannin, Analysis of electrodes' placement and deformation in deep brain stimulation from medical images, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, pp.8316-8348
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F. Lalys, L. Riffaud, X. Morandi, P. I. Jannin, and S. Geneve, Automatic Phases Recognition in Pituitary Surgeries by Microscope Images Classification, pp.34-44
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F. Lalys, C. Haegelen, A. Abadie, and P. Jannin, Post-operative assessment in Deep Brain Stimulation based on multimodal images: registration workflow and validation, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
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F. Lalys, C. Haegelen, M. Baillieul, A. Abadie, and P. Jannin, Anatomo-clinical atlases in subthalamic Deep Brain Stimulation correlating clinical data and electrode contacts coordinates, IBMISPS
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A. Dépôt, D. Bouget, P. Jannin, and L. Fjames, Des informations binaires de présence d'instruments sont analysées et des modèles graphiques probabilistes sont utilisés pour reconnaître des informations de haut niveau dans la salle d'opération. D'autres systèmes ont aussi été testés, comme la mise en place d'un outil de suivi du regard du chirurgien Le principal défaut de tous ces systèmes est qu'ils ne sont pas installés d'office dans les salles d'opération, et que la mise en place de trop nombreux outils pourrait à long terme gêner le déroulé de l'intervention. Pour pallier à ce problème, les nouvelles études se focalisent sur des sources d'informations déjà installées dans la salle d'opération, telles que les signes vitaux des patients L'utilisation de vidéos, grand champs ou endoscopiques, permet d'automatiser l'acquisition de données sans altérer la routine clinique, ProcSide: software for recording surgical procedures ou d'un système de tracking 3D de la positon de chaque membre du staff Des outils de vision par ordinateur et de réalité augmentée sont utilisés pour extraire des informations pertinentes au chirurgien. Les images vidéos des différentes caméras se révèlent donc être une source riche en informations pouvant éventuellement remplacer les approches se basant sur des enregistrements humains, 2003.

. Deuxièmement, nous avons utilisé comme unique source d'information les vidéos des microscopes, utilisés de façon systématique

. Troisièmement, différents niveaux de granularités des tâches chirurgicales (i.e. phases et activités) ont été couverts. Enfin, nous avons introduit une sémantique forte à notre modélisation

. La-chirurgie-de-la-cataracte,-type-de-chirurgie-ophtalmologique, Le principe est d'enlever la lentille naturelle de l'oeil (le cristallin) pour la remplacer par une lentille artificielle Nous disposions de 20 vidéos (temps moyen de chirurgie: 15min) et huit phases furent identifiées (Figure 1, droite) Pour définir les activités, nous nous sommes basés sur la formalisation proposée par Neumuth décrivant une activité comme un triplet : < verbe d'action ? outil chirurgical ? structure anatomique >. 12 verbes d'action, 13 outils chirurgicaux et 6 zones d'action furent identifiés. Toutes les combinaisons ne sont bien évidemment pas possibles, car n'ayant aucun sens, ce qui a amené à identifier 17 activités puis 25 paires d'activités possibles, 2007.

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