Report Pair

Report pair research focuses on leveraging the combined information from medical images and their corresponding textual reports to improve various medical image analysis tasks. Current efforts concentrate on developing and adapting large language models and vision-language pre-training frameworks, often incorporating techniques like contrastive learning, adapter tuning, and generative adversarial networks, to bridge the gap between image and text data. This work aims to improve diagnostic accuracy, automate report generation, and enable tasks like multi-organ segmentation and image synthesis from less expensive modalities, ultimately enhancing healthcare efficiency and patient care.