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- W2748648140 abstract "The treatment of valvular heart disease has shifted from open-heart surgery towards minimally invasive procedures. Without a direct access to the affected anatomy, pre-operative planning and procedural guidance is crucial for a successful outcome. For pre-operative planning we present a novel patient-specific model of the valvular apparatus in combination with a machine learning framework to estimate the model parameters and derive advanced clinical measurements based on the estimated models. Further we introduce a robust model-based fusion framework to fuse high-quality pre-operative modalities with low-quality intra-operative images for intra-operative guidance. Both methods have the potential to improve the treatment outcome while lowering procedural risks and treatment costs." @default.
- W2748648140 created "2017-08-31" @default.
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- W2748648140 date "2014-01-01" @default.
- W2748648140 modified "2023-09-27" @default.
- W2748648140 title "Advanced Valve Modeling and Multi-Modal Fusion for Minimally Invasive Valve Procedures" @default.
- W2748648140 hasPublicationYear "2014" @default.
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