Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images
Abstract In this paper, we propose a deep super-resolution generative adversarial network (DSR-GAN) combined with a convolutional neural network (CNN) model designed to classify four stages of Alzheimer’s disease (AD): Mild Dementia (MD), Moderate Dementia (MOD), Non-Demented (ND), and Very Mild Dem...
Saved in:
| Main Authors: | Sarah Oraby, Ahmed Emran, Basel El-Saghir, Saeed Mohsen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-94677-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Early diagnosis of Alzheimer’s disease using dual GAN model with pyramid attention networks
by: Yinjun Zhang, et al.
Published: (2024-12-01) -
Novel deep learning for multi-class classification of Alzheimer’s in disability using MRI datasets
by: Sumaiya Binte Shahid, et al.
Published: (2025-08-01) -
DHCT-GAN: Improving EEG Signal Quality with a Dual-Branch Hybrid CNN–Transformer Network
by: Yinan Cai, et al.
Published: (2025-01-01) -
Investigating the effect of loss functions on single-image GAN performance
by: Eyyup YİLDİZ, et al.
Published: (2024-12-01) -
Adaptive Elastic GAN for High-Fidelity Blood Cell Image Hallucination and Classification
by: Issac Neha Margret, et al.
Published: (2025-01-01)