Towards a pancreatic surgery simulator based on model order reduction

In this work a pancreatic surgery simulator is developed that provides the user with haptic feedback. The simulator is based on the use of model order reduction techniques, particularly Proper Generalized Decomposition methods. The just developed simulator presents some notable advancements with respect to existing works in the literature, such as the consideration of non-linear hyperelasticity for the constitutive modeling of soft tissues, an accurate description of contact between organs and momentum and energy conserving time integration schemes. Pancreas, liver, gall bladder, and duodenum are modeled in the simulator, thus providing with a very realistic and immersive perception to the user

Serial FEM/XFEM-Based Update of Preoperative Brain Images Using Intraoperative MRI

Current neuronavigation systems cannot adapt to changing intraoperative conditions over time. To overcome this limitation, we present an experimental end-to-end system capable of updating 3D preoperative images in the presence of brain shift and successive resections. The heart of our system is a nonrigid registration technique using a biomechanical model, driven by the deformations of key surfaces tracked in successive intraoperative images. The biomechanical model is deformed using FEM or XFEM, depending on the type of deformation under consideration, namely, brain shift or resection. We describe the operation of our system on two patient cases, each comprising five intraoperative MR images, and we demonstrate that our approach significantly improves the alignment of nonrigidly registered images

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

GPU Implementation of extended total Lagrangian explicit (gpuXTLED) for Surgical Incision Application

An extended total Lagrangian explicit dynamic (XTLED) is presented as a potential numerical method for simulating interactive or physics-based surgical incisions of soft tissues. The simulation of surgical incision is vital to the integrity of virtual reality simulators that are used for immersive surgical training. However, most existing numerical methods either compromise on computational speed for accuracy or vice versa. This is due to the challenge of modelling nonlinear behaviour of soft tissues, incorporating incision and subsequently updating topology to account for the incision. To tackle these challenges, XTLED method which combines the extended finite element method (XFEM) using total Lagrangian formulation with explicit time integration method was developed. The algorithm was developed and deformations of 3D geometries under tension, were simulated. An attempt was made to validate the XTLED method using silicon samples with different incision configuration and a comparison was made between XTLED and FEM. Results show that XTLED could potentially be used to simulate interactive soft tissue incision. However, further quantitative verification and validation are required. In addition, numerical analyses conducted show that solutions may not be obtainable due to simulation errors. However, it is unclear whether these errors are inherent in the XTLED method or the algorithm created for the XTLED method in this thesis

Real-time Biomechanical Modeling for Intraoperative Soft Tissue Registration

Computer assisted surgery systems intraoperatively support the surgeon by providing information on the location of hidden risk and target structures during surgery. However, soft tissue deformations make intraoperative registration (and thus intraoperative navigation) difficult. In this work, a novel, biomechanics based approach for real-time soft tissue registration from sparse intraoperative sensor data such as stereo endoscopic images is presented to overcome this problem