In PET imaging, the amount of radiotracer dose typically correlates with the level of image quality. But researchers from Stanford University have trained a deep-learning algorithm to process ultralow-dose PET image data and then create synthetic images that approximate PET scans acquired using a standard radiotracer dose. The synthetic images using only 1% of current dose levels yielded comparable image quality to standard full-dose exams. Thes artificial intelligence (AI) methods could speed exam times, decrease radiation exposure, lower costs, and alleviate shortages in radiotracers.
