Deep Learning with Transfer Learning for Automated Glaucoma Detection in Fundus Images
Glaucoma is a leading cause of irreversible blindness, making early and accurate detection essential for effective management. This study investigates the use of deep learning for automated glaucoma diagnosis using fundus images from the JustRAIGS challenge dataset, which includes 101442 gradable i...
Saved in:
| Main Authors: | Ruxandra-Mădălina FLORESCU, Dragoş-Ovidiu ALEXANDRU, Mircea-Sebastian ŞERBĂNESCU |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca
2025-05-01
|
| Series: | Applied Medical Informatics |
| Subjects: | |
| Online Access: | https://ami.info.umfcluj.ro/index.php/AMI/article/view/1185 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Framework for Early Detection of Glaucoma in Retinal Fundus Images Using Deep Learning
by: Murali Govindan, et al.
Published: (2024-02-01) -
Novel Deep Learning Model for Glaucoma Detection Using Fusion of Fundus and Optical Coherence Tomography Images
by: Saad Islam, et al.
Published: (2025-07-01) -
Enhanced Privacy-Preserving Architecture for Fundus Disease Diagnosis with Federated Learning
by: Raymond Jiang, et al.
Published: (2025-03-01) -
Hybrid Deep Learning Model for Improved Glaucoma Diagnostic Accuracy
by: Nahum Flores, et al.
Published: (2025-07-01) -
Deep learning-based classification of multiple fundus diseases using ultra-widefield images
by: Ming-Ming Duan, et al.
Published: (2025-07-01)