A Method to Compute Respiration Parameters for Patient-based Simulators

We propose a method to automatically tune a patient-based virtual environment training simulator for abdominal needle insertion. The key attributes to be customized in our framework are the elasticity of soft-tissues and the respiratory model parameters. The estimation is based on two 3D Computed Tomography (CT) scans of the same patient at two different time steps. Results are presented on four patients and show that our new method leads to better results than our previous studies with manually tuned parameters.

[1]  Touradj Ebrahimi,et al.  MESH: measuring errors between surfaces using the Hausdorff distance , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[2]  Nigel W. John,et al.  Simulation of ultrasound guided needle puncture using patient specific data with 3D textures and volume haptics , 2008, Comput. Animat. Virtual Worlds.

[3]  Fernando Bello,et al.  Percutaneous Transhepatic Cholangiography Training Simulator with Real-time Breathing Motion , 2008 .

[4]  Serge Miguet,et al.  Patient setup error measurement using 3D intensity-based image registration techniques. , 2003, International journal of radiation oncology, biology, physics.

[5]  Alessandro Nava,et al.  In vivo mechanical characterization of human liver , 2008, Medical Image Anal..

[6]  Ying Li,et al.  Soft Object Modelling with Generalised ChainMail — Extending the Boundaries of Web‐based Graphics , 2003, Comput. Graph. Forum.

[7]  B. V. Van Beers,et al.  Liver fibrosis: non‐invasive assessment with MR elastography , 2006, NMR in biomedicine.

[8]  J Moseley,et al.  Contact surface and material nonlinearity modeling of human lungs , 2008, Physics in medicine and biology.

[9]  Fernando Bello,et al.  Challenges realising effective radiological interventional virtual environments: the CRaIVE approach. , 2004, Studies in health technology and informatics.

[10]  Derek R. Magee,et al.  An augmented reality simulator for ultrasound guided needle placement training , 2007, Medical & Biological Engineering & Computing.