Recent advances in imaging techniques have enabled us to visualize lung tumors or nodules in early-stage cancer. However, the positions of nodules can change because of intraoperative lung deflation, and the modeling of pneumothorax-associated deformation remains a challenging issue for intraoperative tumor localization. In this study, we introduce spatial and geometric analysis methods for inflated/deflated lungs and discuss heterogeneity in pneumothorax-associated deformation. Contrast-enhanced CT images simulating intraoperative conditions were acquired from live Beagle dogs. Deformable mesh registration techniques were designed to map the surface and subsurface tissues of lung lobes. The developed framework addressed local mismatches of bronchial tree structures and achieved stable registration with a Hausdorff distance of less than 1 mm and a target registration error of less than 5 mm. Our results show that the strain of lung parenchyma was 35% higher than that of bronchi, and that subsurface deformation in the deflated lung is heterogeneous.