Anatomy and Physiology of Artificial Intelligence in PET Imaging
Tyler J. Bradshaw Alan B. McMillan
The influence of artificial intelligence (AI) within the field of nuclear
medicine has been rapidly growing. Many researchers and clinicians are seeking
to apply AI within PET, and clinicians will soon find themselves engaging with
AI-based applications all along the chain of molecular imaging, from image
reconstruction to enhanced reporting. This expanding presence of AI in PET
imaging will result in greater demand for educational resources for those
unfamiliar with AI. The objective of this article to is provide an illustrated
guide to the core principles of modern AI, with specific focus on aspects that
are most likely to be encountered in PET imaging. We describe convolutional
neural networks, algorithm training, and explain the components of the commonly
used U-Net for segmentation and image synthesis.