Enhancing magnetic resonance imaging-driven Alzheimer’s disease classification performance using generative adversarial learning

Enhancing magnetic resonance imaging-driven Alzheimer’s disease classification performance using generative adversarial learning

Abstract Background Generative adversarial networks (GAN) can produce images of improved quality but their ability to augment image-based classification is not fully explored. We evaluated if a modified GAN can learn from magnetic resonance imaging (MRI) scans of multiple magnetic field strengths to...

Full description

Bibliographic Details
Main Authors: Xiao Zhou, Shangran Qiu, Prajakta S. Joshi, Chonghua Xue, Ronald J. Killiany, Asim Z. Mian, Sang P. Chin, Rhoda Au, Vijaya B. Kolachalama
Format: Article
Language:English
Published: BMC 2021-03-01
Series:Alzheimer’s Research & Therapy
Subjects:
Alzheimer’s disease
Magnetic resonance imaging
Magnetic field strength
Deep learning
Generative adversarial network
Fully convolutional network
Online Access:https://doi.org/10.1186/s13195-021-00797-5

Internet

https://doi.org/10.1186/s13195-021-00797-5

Similar Items