In diesem Wintersemester wird die im WiSe 2022/23 erfolgreich gestartete Vortragsreihe 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Information Sciences fortgesetzt. Renommierte Wissenschaftlerinnen und Wissenschaftler unterschiedlicher Fachdisziplinen und Forschungsstandorte geben jeden Donnerstag ab 16:00 Uhr Einblicke in aktuelle Fragestellungen und Anwendungsgebiete des breiten Forschungsfeldes 威尼斯赌博游戏_威尼斯赌博app-【官网】ical Information Sciences.

Human trabecular bone is a structural, calcified tissue of struts and plates with cavities containing bone marrow. Determining its mechanical properties can support the design of patient-specific implants, e.g., for total hip- or knee arthroplasties. The effective stiffness is obtainable based on the direct discretization of microfocus computed tomography (mCT) data. However, the Finite Element Analysis (FEA) based analytical approach is computationally expensive and requires high-performance computing (HPC) resources that are unsuitable in daily clinical context. Our research introduces an artificial intelligence (AI) centric method to determine the effective stiffness of human trabeculae with sufficient accuracy at a fraction of the computational cost of current analytical implementations. This talk furthermore shows the data, training process, and validation of the biomechanical results with the analytical state-of-the-art method as the ground truth. Furthermore, we will describe the limits and outlook for contributing to patient-specific mechanical characterizations.