Implicitly Solved Regularization for Learning-Based Image Registration

Jan Ehrhardt, Heinz Handels

Abstract: Deformable image registration is a fundamental step in many medical image analysis tasks and has attracted a large amount of research to develop efficient and accurate unsupervised machine learning approaches. Although much attention has been paid to finding suitable similarity measures, network architectures and training methods, much less research has been devoted to suitable regularization techniques to ensure the plausibility of the learned deformations.