Pre-training 3D convolutional neural networks for prodromal alzheimer's disease classification
Alzheimer's disease (AD) is a chronic neurodegenerative disease that causes cognitive deficits, which severely interfere with daily life. Convolutional Neural Networks (CNNs) have been used to analyze Medical Resonance Imaging (MRI) scans for the early detection of AD. Prior works have explored...
Saved in:
Main Authors: | Jiang, Hongchao, Miao, Chunyan |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/159700 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
BRAIN WHITE MATTER ABNORMALITIES IN PRODROMAL AND CLINICAL ALZHEIMER'S DISEASE
by: JI, FANG
Published: (2018) -
Tienma and Alzheimer's disease
by: Huang, Junjie
Published: (2013) -
A highly predictive signature of cognition and brain atrophy for progression to Alzheimer's dementia.
by: Tam, Angela, et al.
Published: (2019) -
MODELING ALZHEIMER'S DISEASE PROGRESSION ON A PATHOLOGICAL TIMELINE
by: CHUA LAIYI
Published: (2017) -
Stability analysis of the ODE model representation of Amyloidogenic processing in Alzheimer's disease in the presence of SORLA
by: Alcantara, Jan Harold Mercado
Published: (2015)