Radiologist Annotation

Radiologist annotation, the process of labeling medical images with diagnostic information, is crucial for training and evaluating AI models in radiology. Current research focuses on improving the efficiency and accuracy of this process, including developing automated annotation tools using large language models (LLMs) to analyze radiology reports and convolutional neural networks (CNNs) and transformers to analyze images, often incorporating techniques like contrastive learning and attention mechanisms. These advancements aim to reduce the time and cost associated with manual annotation, ultimately leading to more accurate and readily available AI-powered diagnostic tools for improved patient care and workflow efficiency in radiology.