A framework for real-time visualization of a tumor-influenced lung dynamics is presented in this paper. This framework potentially allows clinical technicians to visualize in 3D the morphological changes of lungs under different breathing conditions. Consequently, this technique may provide a sensitive and accurate assessment tool for preoperative and intra-operative clinical guidance. The proposed simulation method extends work previously developed for modeling and visualizing normal 3D lung dynamics. The model accounts for the changes in the regional lung functionality and the global motor response due to the presence of a tumor. For real-time deformation purposes, we use a Green\u27s function (GF), a physically based approach that allows real-time multi-resolution modeling of the lung deformations. This function also allows an analytical estimation of the GF\u27s deformation parameters from the 4D lung datasets at different level-of-details of the lung model. Once estimated, the subject-specific GF facilitates the simulation of tumor-influenced lung deformations subjected to any breathing condition modeled by a parametric Pressure-Volume (PV) relation
