Abdominal CT Registration

Abdominal CT registration aims to precisely align different abdominal CT scans, crucial for tasks like disease monitoring and surgical planning. Current research focuses on improving accuracy and efficiency using deep learning models, such as variations of U-Nets and transformer-based architectures, often incorporating techniques like weighted attention mechanisms and adaptive loss weighting to handle the complex anatomical variability of the abdomen. These advancements leverage both image features and anatomical priors (e.g., from segmentations or text prompts) to achieve robust and computationally feasible registration, ultimately improving the precision and reliability of medical image analysis.