Deep learning improves utility of tau PET in the study of Alzheimer's disease
Abstract
Positron emission tomography (PET) imaging targeting neurofibrillary tau tangles is increasingly used in the study of Alzheimer's disease (AD), but its utility may be limited by conventional quantitative or qualitative evaluation techniques in earlier disease states. Convolutional neural networks (CNNs) are effective in learning spatial patterns for image classification.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2021
- Source ID
- 10.1002/dad2.12264
Entities
People
- Adam M. Brickman
- Aubrey Johnson
- David Park
- Devangere P. Devanand
- For The Alzheimer’s Disease Neuroimaging Initiative*
- Frank A. Provenzano
- James Zou
- Jeanelle France
- José A. Luchsinger
- Michelle Pardo
- William C. Kreisl
- Xinyang Feng
- Zeljko Tomljanovic
Organizations
- Columbia University
- National Institutes of Health