Artificial CT images can enhance variation of case images in diagnostic radiology skills training

ConclusionArtificial images can be generated in a way such that they blend in with original images and adhere to anatomical constraints, which can be manipulated to augment the variability of cases.Critical relevance statementArtificial medical images can be used to enhance the availability and variety of medical training images by creating new but comparable images that can blend in with original images.Key points• Artificial images, similar to original ones, can be created using generative networks.• Pathological features of artificial images can be adjusted through guiding the network.• Artificial images proved viable to augment the depth and broadening of diagnostic training.Graphical Abstract
Source: Insights into Imaging - Category: Radiology Source Type: research