Groupwise Registration

Groupwise registration aims to simultaneously align multiple images, overcoming limitations of pairwise methods that register images one at a time. Current research emphasizes deep learning approaches, often employing architectures like variational autoencoders or leveraging keypoint-based models, to achieve robust and efficient registration across diverse modalities and large datasets. These advancements improve accuracy and speed, particularly for challenging applications like longitudinal studies of disease progression or motion correction in dynamic imaging, leading to more reliable quantitative analyses in medical image analysis. The resulting improvements in image alignment facilitate more accurate and efficient medical image analysis across various applications.