Towards an efficient data assimilation in physically-based medical simulations

Computer simulation of soft tissues is rapidly becoming an important aspect of medical training, pre-operative planning and intra-operative navigation. Whereas in medical training, generic models are usually employed, both planing and navigation require patient-specific modeling. However, creating a patient-specific model is a challenging task, as many of the mechanical parameters of the organ tissues are unknown. One way of addressing the issue is to extend the deterministic simulation by methods based on stochastic modeling.