A survey on deep learning in medical image registration: new technologies, uncertainty, evaluation metrics, and beyond

Understand

Deep learning technologies have dramatically reshaped the field of medical image registration over the past decade.

• The initial developments, such as regression-based and U-Net-based networks, established the foundation for deep learning in image registration.
• Subsequent progress has been made in various aspects of deep learning-based registration, including similarity measures, deformation regularizations, network architectures, and uncertainty estimation.
• These advancements have not only enriched the field of image registration but have also facilitated its application in a wide range of tasks, including atlas construction, multi-atlas segmentation, motion estimation, and 2D-3D registration.