Abstract
Automatic image registration plays an important role in many aspects of the radiation oncology workflow ranging from treatment simulation, image guided and adaptive radiotherapy, motion management and response evaluation. Traditional automatic registration algorithms are often time-consuming and further improvements in registration accuracy are required. Recently, a variety of AI-driven strategies for automatic image registrations have been developed. In this review an overview of the many applications of automatic image registration in radiation oncology is provided. Different learning strategies and network architectures have been reviewed and the current status of AI based automatic image registration algorithms in radiation oncology has been described. AI based strategies for automatic image registration typically do not outperform traditional strategies yet. Various promising approaches to further improve AI based image registrations are being explored. Therefore AI based automatic image registration may be the method of choice in the foreseeable future.