Chest X Ray
Chest X-ray (CXR) analysis is a crucial diagnostic tool in healthcare, with research focusing on improving accuracy, efficiency, and accessibility of interpretation. Current efforts center on developing and refining deep learning models, including convolutional neural networks (CNNs) and vision transformers (ViTs), often incorporating techniques like transfer learning, self-supervised learning, and multi-modal approaches that integrate textual reports and other patient data. These advancements aim to automate report generation, improve disease detection (including in under-resourced settings), and enhance the overall quality and speed of radiological diagnosis, ultimately impacting patient care and clinical workflow.
Papers
Routine Usage of AI-based Chest X-ray Reading Support in a Multi-site Medical Supply Center
Karsten Ridder, Alexander Preuhs, Axel Mertins, Clemens Joerger
How many radiographs are needed to re-train a deep learning system for object detection?
Raniere Silva, Khizar Hayat, Christopher M Riggs, Michael Doube