作者: Pierre-Frédéric Villard , Fernando Bello , Nigel W. John , Franck Patrick Vidal
DOI: 10.3233/978-1-61499-022-2-529
关键词: Needle insertion 、 Simulation 、 Computed tomography 、 Computer vision 、 Artificial intelligence 、 Computer science
摘要: We propose a method to automatically tune patient-based virtual environment training simulator for abdominal needle insertion. The key attributes be customized in our framework are the elasticity of soft-tissues and respiratory model parameters. estimation is based on two 3D Computed Tomography (CT) scans same patient at different time steps. Results presented four patients show that new leads better results than previous studies with manually tuned