Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

THIS WEBPAGE IS DEPRECATED - please visit our new website

B. Fuerst, T. Mansi, P. Khurd, T. Zhang, J. Declerck, T. Boettger, N. Navab, J. Bayouth, A. Kamen
Patient-Specific Finite-Element Simulation of Respiratory Mechanics for Radiotherapy Guidance, A First Evaluation Study
IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2012), Barcelona, Spain, May 2 - 5, 2012 (bib)

During radiotherapy of lung tumors, the respiratory motion must be tracked to reduce radiation of healthy tissue. This is usually done by using a respiratory surrogate, but with limited accuracy. We investigate how patient-specific finite element models (FEM) of respiratory mechanics can predict the motion of the lungs. First, the anatomical models of the lungs and thorax are extracted from CT images automatically. Then, a biomechanical model is used to simulate the respiratory motion based on a novel thorax/lung interaction force that simulates the pleural cavity. Our model is not driven by image forces but by thoracic pressures personalized using a multivariate optimizer. The proposed model is validated on three DIR-Lab datasets, yielding a promising internal land- mark error of 3.33 ± 0.60 mm. Our model may represent a tool for lung deformation prediction and therapy guidance.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif