naa a22 4500 510806945 CHVBK 20180411083422.0 cr unu---uuuuu 180411e20130101xx s 000 0 eng 10.1007/s11548-012-0685-6 doi (NATIONALLICENCE)springer-10.1007/s11548-012-0685-6 Automatic knowledge-based recognition of low-level tasks in ophthalmological procedures [Elektronische Daten] [Florent Lalys, David Bouget, Laurent Riffaud, Pierre Jannin] Purpose: Surgical process models (SPMs) have recently been created for situation-aware computer-assisted systems in the operating room. One important challenge in this area is the automatic acquisition of SPMs. The purpose of this study is to present a new method for the automatic detection of low-level surgical tasks, that is, the sequence of activities in a surgical procedure, from microscope video images only. The level of granularity that we addressed in this work is symbolized by activities formalized by triplets <action, surgical tool, anatomical structure>. Methods: Using the results of our latest work on the recognition of surgical phases in cataract surgeries, and based on the hypothesis that most activities occur in one or two phases only, we created a light-weight ontology, formalized as a hierarchical decomposition into phases and activities. Information concerning the surgical tools, the areas where tools are used and three other visual cues were detected through an image-based approach and combined with the information of the current surgical phase within a knowledge-based recognition system. Knowing the surgical phases before the activity, recognition allows supervised classification to be adapted to the phase. Multiclass Support Vector Machines were chosen as a classification algorithm. Results: Using a dataset of 20 cataract surgeries, and identifying 25 possible pairs of activities, a frame-by-frame recognition rate of 64.5 % was achieved with the proposed system. Conclusions: The addition of human knowledge to traditional bottom-up approaches based on image analysis appears to be promising for low-level task detection. The results of this work could be used for the automatic indexation of post-operative videos. CARS, 2012 Surgical workflow nationallicence Activity detection nationallicence Surgical ontology nationallicence Image-based analysis nationallicence Surgical process model nationallicence Lalys Florent MedICIS, INSERM, U1099, Faculté de Médecine CS 34317, University of Rennes I, 2 Av. du Pr Leon Bernard, 35043, Rennes Cedex, France aut Bouget David MedICIS, INSERM, U1099, Faculté de Médecine CS 34317, University of Rennes I, 2 Av. du Pr Leon Bernard, 35043, Rennes Cedex, France aut Riffaud Laurent Department of Neurosurgery, Pontchaillou University Hospital, 35043, Rennes, France aut Jannin Pierre MedICIS, INSERM, U1099, Faculté de Médecine CS 34317, University of Rennes I, 2 Av. du Pr Leon Bernard, 35043, Rennes Cedex, France aut International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/1(2013-01-01), 39-49 1861-6410 8:1<39 2013 8 11548 https://doi.org/10.1007/s11548-012-0685-6 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-012-0685-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Lalys Florent MedICIS, INSERM, U1099, Faculté de Médecine CS 34317, University of Rennes I, 2 Av. du Pr Leon Bernard, 35043, Rennes Cedex, France aut NATIONALLICENCE 700 1- Bouget David MedICIS, INSERM, U1099, Faculté de Médecine CS 34317, University of Rennes I, 2 Av. du Pr Leon Bernard, 35043, Rennes Cedex, France aut NATIONALLICENCE 700 1- Riffaud Laurent Department of Neurosurgery, Pontchaillou University Hospital, 35043, Rennes, France aut NATIONALLICENCE 700 1- Jannin Pierre MedICIS, INSERM, U1099, Faculté de Médecine CS 34317, University of Rennes I, 2 Av. du Pr Leon Bernard, 35043, Rennes Cedex, France aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/1(2013-01-01), 39-49 1861-6410 8:1<39 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer