MEDIASSIST: medical assistance for intraoperative skill transfer in minimally invasive surgery using augmented reality

Abstract

Minimally invasive surgery is a highly complex medical discipline with various risks for surgeon and patient, but has also numerous advantages on patient-side. The surgeon has to adapt special operation-techniques and deal with difficulties like the complex hand-eye coordination, limited field of view and restricted mobility. To alleviate with these new problems, we propose to support the surgeon's spatial cognition by using augmented reality (AR) techniques to directly visualize virtual objects in the surgical site. In order to generate an intelligent support, it is necessary to have an intraoperative assistance system that recognizes the surgical skills during the intervention and provides context-aware assistance surgeon using AR techniques. With MEDIASSIST we bundle our research activities in the field of intraoperative intelligent support and visualization. Our experimental setup consists of a stereo endoscope, an optical tracking system and a head-mounted-display for 3D visualization. The framework will be used as platform for the development and evaluation of our research in the field of skill recognition and context-aware assistance generation. This includes methods for surgical skill analysis, skill classification, context interpretation as well as assistive visualization and interaction techniques. In this paper we present the objectives of MEDIASSIST and first results in the fields of skill analysis, visualization and multi-modal interaction. In detail we present a markerless instrument tracking for surgical skill analysis as well as visualization techniques and recognition of interaction gestures in an AR environment.