CT IMAGE-BASED METHOD AND DEVICE FOR REALIZING LUNG NODULE ADAPTIVE MATCHING BY BONE REGISTRATION

摘要

A CT image-based method for realizing lung nodule adaptive matching by bone registration, comprising the following steps: data preparation, extraction of lung and bone point cloud data, three-dimensional point cloud data registration, and lung nodule adaptive matching. In said method, firstly, three-dimensional point cloud rigid transformation registration is performed on lung image data and lung nodule data on the basis of the characteristic of small changes in human bone, so as to achieve the alignment of the lung and the lung nodule data before and after follow-up; secondly, an FGR algorithm is used, and in terms of operation speed and registration accuracy, the FGR algorithm is obviously superior to local refinement algorithms such as ICP; thirdly, the RMSE is used as a lung point cloud registration error, achieving lung nodule adaptive matching, so that the lung nodule registration requires less manual intervention, has a high degree of automation, and achieves an accurate registration resu and fourthly, normalization processing is performed on CT image data, so that the robustness of the algorithm can be improved. The method can be widely applied to CT devices of different models and DICOM data of different pixel spacing values.