LungRegNet: An unsupervised deformable image registration method for 4D‐CT lung

Purpose To develop an accurate and fast deformable image registration (DIR) method for four‐dimensional computed tomography (4D‐CT) lung images. Deep learning‐based methods have the potential to quickly predict the deformation vector field (DVF) in a few forward predictions. We have developed an unsupervised deep learning method for 4D‐CT lung DIR with excellent performances in terms of registration accuracies, robustness, and computational...