AmyloidPETNet: Classification of Amyloid Positivity in Brain PET Imaging Using End-to-End Deep Learning
Shuyang Fan, Maria Rosana Ponisio, Pan Xiao, Sung Min Ha, Satrajit Chakrabarty, John J. Lee, Shaney Flores, Pamela LaMontagne, Brian A. Gordon, Cyrus A. Raji, Daniel S. Marcus, Arash Nazeri, Beau M. Ances, Randall J. Bateman, John C. Morris, Tammie L.S. Benzinger, Aristeidis Sotiras, for the Alzheimer's Disease Neuroimaging Initiative
Abstract
An end-to-end deep learning method accurately classified amyloid positivity in native-space brain PET scans acquired using five different tracers and across five independent data sets, without requiring structural MRI.
Topics & Concepts
MedicineAmyloid (mycology)NeuroimagingPositron emission tomographyNuclear medicineArtificial intelligencePathologyPsychiatryComputer scienceMedical Imaging Techniques and ApplicationsFunctional Brain Connectivity StudiesBrain Tumor Detection and Classification