The estimation and correction of lung respiratory motions are crucial for the image-guided radiotherapy of lung cancer, which require motion displacement information obtained using the image registration technology. However, lungs are typical moving organs that involve complex deformations during the breathing cycle, owing to which the three-dimensional computed tomography (CT) image registration of lungs becomes difficult and time-consuming. Currently, the registration of lung CT images remains a challenge that requires urgent attentions. In this study, a nonuniform B-spline image registration method based on the adaptive regularization term is proposed. First, a nonuniform B-spline deformation model is constructed, in which the control point gird is initialized using spatial adaptive sparsity based on the curvature according to the characteristics of the physiological structure of the lung to improve the registration efficiency. Furthermore, by designing the spatial position weights of the pixel points, the smooth regularization and total variation regularization terms of the deformation field are adaptively combined to improve the registration accuracy. The effectiveness of the proposed method is verified via experiments on public data sets and comparison with some other registration methods.