PhD defense : Preoperative path planning and optimization in static and deformable conditions for image-guided minimally invasive surgery

PhD defense : Noura HAMZE

Team : IGG

Title : Preoperative path planning and optimization in static and deformable conditions for image-guided minimally invasive surgery

Abstract : In image-guided minimally invasive surgery, a precise preoperative planning of the surgical tools trajectory is a key factor to a successful intervention. However, an efficient planning is a challenging task, which can be significantly improved when considering different contributing factors such as biomechanical intra-operative deformations, or novel optimization techniques. In this work, we focus on two aspects. The first aspect addresses integrating intra-operative deformation to the path planning process. Our methods combine geometric-based optimization techniques with physics-based simulations. They are characterized with a certain level of generality, and are experimented on two different surgical procedures: percutaneous procedures for hepatic tumor ablation, and in neurosurgery for Deep Brain Stimulation (DBS). Secondly, we investigate, implement, and compare many optimization approaches using qualitative and quantitative methods, and present an efficient evolutionary Pareto-based multi-criteria optimization method which can find optimal solutions that are not reachable via the current state of the art methods.

This thesis was supervised by Caroline Essert (ICube).

The presentation will take place on Tuesday, June 21th at 9.30am in room A207 of the pole API building in Illkirch. This thesis will be supported in english.