Generative adversarial network constrained multiple loss autoencoder: A deep learning‐based individual atrophy detection for Alzheimer's disease and mild cognitive impairment

Exploring individual brain atrophy patterns is of great value in precision medicine for Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, the current individual brain atrophy detection models are deficient. Here, we proposed a framework called generative adversarial network...

Full description

Saved in:

Bibliographic Details
Published in:	Human brain mapping Vol. 44; no. 3; pp. 1129 - 1146
Main Authors:	Shi, Rong, Sheng, Can, Jin, Shichen, Zhang, Qi, Zhang, Shuoyan, Zhang, Liang, Ding, Changchang, Wang, Luyao, Wang, Lei, Han, Ying, Jiang, Jiehui
Format:	Journal Article
Language:	English
Published:	Hoboken, USA John Wiley & Sons, Inc 15.02.2023
Subjects:	Alzheimer Disease - pathology Alzheimer's disease Atrophy Atrophy - diagnostic imaging Atrophy - pathology Automation Brain Brain - diagnostic imaging Brain - pathology Cognitive ability Cognitive Dysfunction - diagnostic imaging Cognitive Dysfunction - pathology Deep Learning Dementia GAN Generative adversarial networks Humans Image processing Image reconstruction Impairment Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Neurodegenerative diseases Neuroimaging Precision medicine Signal to noise ratio Signs and symptoms Subgroups precision medicine magnetic resonance imaging GAN Alzheimer's disease
ISSN:	1065-9471, 1097-0193, 1097-0193
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!