Double-low-dose CT combined with deep learning image reconstructions (DLIR) achieves coronary mixed reality data source optimization

Introduction Mixed reality combines the advantages of augmented reality and virtual reality technology into one image and can display the patient’s three-dimensional (3D) image in front of the user’s eyes using the main data source of coronary computed tomography (CT) data. Therefore, when acquiring a coronary mixed reality data source, the issues of radiation dose and contrast media dose must be considered. Methods In our study, we adopted double-low-dose CT (80 kVp, iodine delivery rate 1.2 g/s) combined with deep learning image reconstructions (DLIR). Results We reduced the radiation dose by 42% and the contrast media dose by 31% while maintaining image quality. We found that the resolution of mixed reality 3D modeling software currently cannot distinguish small differences in data sources. With improvements in 3D modeling software resolution, the display of small differences in data sources will become more significant. Discussion These findings provide actionable directions for future research and collaborative development of coronary mixed reality content and features.