Image-guided surgery systems can be improved by the knowledge of surgical expertise. The more the surgeon and the system know about the surgical procedure to perform beforehand, the easier it will be to plan and perform. The main objective of this paper is to introduce an approach for predicting surgical performance according to input variables related to the patient. This prediction is a first step towards the inclusion of surgical expertise in the image guided surgery systems. We previously proposed a generic model for describing surgical procedures in the specific context of multimodal neuronavigation. In this paper, we present the preliminary results of the analysis of a neurosurgical cases database built in accordance with the generic model and including 159 surgical cases concerning right-handed patients. We defined two queries on this surgical cases database to illustrate how it could be used to extract relevant and conclusive information about the surgical procedures: How does the anatomical localization of the target influence patient positioning? How does the anatomical localization of the target influence progress of the steps involved in the surgical procedure? The mid-term goal of our research is to semi automatically extract information, a priori models or scenarios of specific surgical procedures that can make easier the decision making process both for planning and surgery.
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