Multi-View Separable Pyramid Network for AD Prediction at MCI Stage by 18F-FDG Brain PET Imaging

• Published in: IEEE transactions on medical imaging Vol. 40; no. 1; pp. 81 - 92
• Main Authors: Pan, Xiaoxi, Phan, Trong-Le, Adel, Mouloud, Fossati, Caroline, Gaidon, Thierry, Wojak, Julien, Guedj, Eric
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Alzheimer's disease; Cognitive ability; Convolution; Decision making; Deep learning; Dementia; Dementia disorders; F-FDG PET; Feature extraction; Fluorine isotopes; Impairment; Machine learning; Magnetic resonance imaging; Medical imaging; mild cognitive impairment; Neurodegenerative diseases; Neuroimaging; Older people; Positron emission; Positron emission tomography; Separable convolution; slice-wise CNN; Spatial data; spatial-wise CNN; Three-dimensional displays; Tomography; Two dimensional displays

Alzheimer's Disease (AD), one of the main causes of death in elderly people, is characterized by Mild Cognitive Impairment (MCI) at prodromal stage. Nevertheless, only part of MCI subjects could progress to AD. The main objective of this paper is thus to identify those who will develop a dement...