Radiology Image

Radiology image analysis focuses on developing automated systems to interpret medical images like X-rays, CT scans, and MRIs, improving diagnostic accuracy and efficiency. Current research emphasizes the development of deep learning models, including convolutional neural networks (CNNs) and transformer-based architectures, often incorporating multimodal data (images and text) and techniques like self-supervised pre-training and attention mechanisms to enhance performance. These advancements aim to address challenges such as data scarcity, variability in image quality, and the need for robust uncertainty quantification, ultimately assisting radiologists and improving patient care.