Practical applications of deep learning: classifying the most common categories of plain radiographs in a PACS using a neural network.
Thomas DratschMichael KorenkovDavid ZopfsSebastian BrodehlBettina BaesslerDaniel GieseSebastian BrinkmannDavid MaintzDaniel Pinto Dos SantosPublished in: European radiology (2020)
• Data from one single institution can be used to train a neural network for the correct detection of the 30 most common categories of plain radiographs. • The trained model achieved a high accuracy for the majority of categories and showed good generalizability to images from other institutions. • The neural network is made publicly available and can be used to automatically organize a PACS or to preselect radiographs so that they can be routed to more specialized neural networks for abnormality detection.