Deformable Image Registration

Deformable image registration (DIR) aims to precisely align images exhibiting non-linear deformations, a crucial task in medical imaging for tasks like treatment planning and disease monitoring. Current research emphasizes improving accuracy and efficiency through novel deep learning architectures, including transformers, diffusion models, and refined convolutional neural networks, often incorporating multi-scale feature fusion and advanced regularization techniques to handle complex deformations and uncertainties. These advancements are significantly impacting medical image analysis by enabling more accurate and robust image alignment, leading to improved diagnostic capabilities and more effective therapeutic interventions.