IMPACT: Images and Models for the Planning and AssistanCe to surgery and Therapy
Team leaders: Pascal HAIGRON (PU) & Renaud DE CREVOISIER (PU-PH)
Areas: Image Guided Therapies - Computer Assisted Interventions
- Cardiovascular therapy
- External radiation therapy
Objective: Optimization and personalization of the interventional strategy
- Moving / deformable anatomical structures
- Pathophysiological observations: pre-/per-/post-treatment, multi-modal, multi-scale
Computer assisted medical and surgical interventions (with either passive, synergistic or active guidance) can largely take benefit of virtual/mixed reality like approaches. Our approach was very early structured within a real/virtual cooperation framework with a generic scope, i.e. transposable to the different physical (or energy-based) therapeutic principles which interest us, whatever their mode of application is (external, interstitial, intra-luminal/cavitary).
Such a scheme involves decision-making loops (critical tasks performed by the user), as well as reactive loops (computational tasks performed by the machine). By integrating more information from heterogeneous data and predictive modelling, our aim is to contribute to the elaboration of new knoweldge and solution to support interventional decision making, which is spread over different timescales and imposes the combination of very-short-term (intra-operative planning and action), short-term (pre-operative planning), and long-term (follow-up, recommendations) analyses.
In this context, our work more specifically addresses the issues of:
- Patient specific analysis to augment target description
- Population analysis for the prediction of therapy outcome
- Real-virtual matching for the adaptation of therapy