Estimation of Inner Lung Motion Fields by Non-linear Registration

Abstract

Detailed analysis of breathing dynamics, as motivated by radiotherapy of lung tumors, requires accurate estimates of inner lung motion fields. We present an evaluation and comparison study of non-linear non-parametric intensity-based registration approaches to estimate these motion fields in 4D CT images. In order to cope with discontinuities in pleura and chest wall motion we restrict the registration by applying lung segmentation masks and evaluate the impact of masking on registration accuracy. Furthermore, we compare diffusive to elastic regularization and diffeomorphic to non-diffeomorphic implementations. Based on a data set of 10 patients we show that masking improves registration accuracy significantly. Moreover, neither elastic or diffusive regularization nor diffeomorphic versus non-diffeomorphic implementation influence the accuracy significantly. Thus, the method of choice depends on the application and requirements on motion field characteristics.