The embodiment of the invention provides a method for realizing pulmonary nodule adaptive matching based on CT image skeleton registration. The method comprises the following steps of data preparation, lung and skeleton point cloud data extraction, three-dimensional point cloud data registration and pulmonary nodule adaptive matching. . Firstly, lung image data and pulmonary nodule data are subjected to three-dimensional point cloud rigid transformation registration based on the characteristic of small human skeleton change characteristics, so that alignment of the lung and pulmonary nodule data before and after follow-up visit is realized. Secondly, an FGR algorithm is adopted, so that the method is obviously superior to ICP and other local refinement algorithms in the aspects of operation speed and registration accuracy. Thirdly, RMSE is adopted as a lung point cloud registration error, adaptive matching of pulmonary nodules is achieved, manual intervention of pulmonary nodule registration is little, the automation degree is high, and the registration result is accurate; and fourthly, normalization processing is carried out on the CT image data, so that the robustness of the algorithm can be improved, and the method can be widely applied to different types of CT equipment and DICOM data with different pixel spacing values.