Registration Algorithm

Image registration algorithms aim to align images from different sources or viewpoints, a crucial step in many scientific and engineering fields. Current research focuses on improving accuracy and efficiency, exploring both classical optimization methods (like ICP and its variants) and deep learning approaches (e.g., U-Nets, transformers), often incorporating techniques like multi-scale processing and feature learning to handle diverse data types and complexities. These advancements are impacting various applications, from medical image analysis (e.g., brain tumor registration, cardiac imaging) and autonomous navigation to remote sensing and industrial quality control, enabling more precise and efficient analyses.