Deformable image registration is a key enabling technology for adaptive radiation therapy (ART) as it can facilitate structure segmentation as well as dose tracking and accumulation. In this work, we develop an efficient inverse-consistent diffeomorphic registration method applying the log-Euclidean formulation of diffeomorphisms. Unlike existing log-Euclidean deformable registration approaches, the proposed method deforms two images towards each other in a completely symmetric fashion during the registration optimization, which leads to higher efficiency and better accuracy in recovering large deformations. The method is applied for the automatic segmentation of daily CT images in prostate ART. To address difficulties caused by large bladder and rectum content change, we propose further improvements and combine deformable registration with model-based image segmentation. Validation results on real clinical data showed that the proposed method gives highly accurate segmentation of interested structures.
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