Data Assimilation for Patient-Specific Physics-based Surgical Simulations
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In the last decade the importance of computer medical simulation in pre-operative planning and intra-operative guidance has increased considerably. The recent advances show that the simulations has become capable of providing efficient improvements in the laparoscopic as well as the open surgery: e.g., the augmented-reality techniques employing a patient-specific model reconstructed from pre-operative data are currently experimented to navigate the surgeon during the intervention. The simulations, however, require models which in turn depends on parameters. While average values are usually reported in the literature, values of some parameters display significant intra-patient variance, thus introducing important uncertainty jeopardizing the accuracy and robustness of modeling.
In our presentation, we focus on method of data assimilation which provide an elegant framework for handling the uncertainties in model parameters. We will give a short description of the state-of-the-art methods and present preliminary results of our research.
Igor Peterlik received his Ph.D. degree in theoretical and applied computer science from Masaryk University, Czech Republic (2009). Between 2009 and 2011, he participated in European project PASSPORT at Inria, France, followed by a post-doctoral internship at the Robotics and Control Lab at the University of British Columbia, Canada. In 2012, he became an investigator of projects focusing on augmented reality for intra-operative navigation at the Institute of Image-Guided Surgery IHU Strasbourg. Currently, he is a permanent researcher at Inria team Mimesis and CNRS laboratory ICube in Strasbourg. His research interests include computational biomechanics, numerical optimization, image-driven simulation, medical image processing and human-computer interaction.
Speaker: Igor Peterlik
VeranstaltungsortUniversité du Luxembourg - Campus Belval
Termin(e) und Uhrzeit(en)
14:00 - 15:00
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