Alterations in the structure and function of the pulmonary system that occur in disease or injury often give rise to measurable spectral, spatial and/or temporal changes in lung sound production and transmission. These changes, if properly quantified, might provide additional information about the etiology, severity and location of trauma, injury, or pathology. With this in mind, the authors are developing a comprehensive computer simulation model of pulmonary acoustics, known as The Audible Human Project™. Its purpose is to improve our understanding of pulmonary acoustics and to aid in interpreting measurements of sound and vibration in the lungs generated by airway insonification, natural breath sounds, and external stimuli on the chest surface, such as that used in elastography. As a part of this development process, finite element (FE) models were constructed of an excised pig lung that also underwent experimental studies. Within these models, the complex airway structure was created via two methods: x-ray CT image segmentation and through an algorithmic means called Constrained Constructive Optimization (CCO). CCO was implemented to expedite the segmentation process, as airway segments can be grown digitally. These two approaches were used in FE simulations of the surface motion on the lung as a result of sound input into the trachea. Simulation results were compared to experimental measurements. By testing how close these models are to experimental measurements, we are evaluating whether CCO can be used as a means to efficiently construct physiologically relevant airway trees.