Medical Image Registration

Medical image registration aims to precisely align images of the same anatomy acquired at different times, from different viewpoints, or using different modalities. Current research heavily emphasizes deep learning approaches, employing convolutional neural networks (CNNs), transformers, and hybrid architectures, often incorporating attention mechanisms and multi-scale processing to improve accuracy and efficiency. These advancements are crucial for improving diagnostic accuracy, treatment planning, and longitudinal disease monitoring across various medical imaging applications, particularly in areas like oncology and cardiology. Furthermore, research is exploring the use of foundation models and physics-informed methods to enhance generalizability and robustness.