Development, Validation, and Modelling of Image Guidance Systems for Surgery

Abstract

Image guidance systems for surgery enable the surgeon to make use of information from various sources during surgery. Such systems have the potential to improve outcomes for patients by allowing the surgeon to easily assimilate prior knowledge from pre-operative clinical scans as well as novel intra-operative imaging techniques. A key challenge is how to filter and process this information to allow it to be presented in an accurate, timely, and intuitive manner. Badly designed or poorly understood image guidance systems risk distracting the surgeon with irrelevant or incorrect information, leading to patient harm. The aim of my research is to develop tools to better quantify the performance of surgical image guidance systems, and measure how the system performance affects patient outcomes. I will present the results of my work developing the “SmartLiver”[1] image guidance system for minimally invasive liver surgery. I will follow this with a proposal for a generalised model of image guidance systems as multi input control systems.