HFF-Net: A hybrid convolutional neural network for diabetic retinopathy screening and grading
Diabetic Retinopathy (DR) is a leading cause of vision loss among diabetic patients, necessitating effective screening and grading for timely intervention. Regular screening significantly increases the workload of ophthalmologists, and accurate grading into stages—mild, moderate, severe, and prolife...
        Saved in:
      
    
          | Main Authors: | Muhammad Hassaan Ashraf, Hamed Alghamdi | 
|---|---|
| Format: | Article | 
| Language: | English | 
| Published: | KeAi Communications Co., Ltd.
    
        2024-12-01 | 
| Series: | Biomedical Technology | 
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949723X24000291 | 
| Tags: | Add Tag 
      No Tags, Be the first to tag this record!
   | 
Similar Items
- 
                
                    Diabetic Retinopathy Classification Using Hybrid Color-Based CLAHE and Blood Vessel in Deep Convolution Neural Network        
                          
 by: Ammar Jawad Kadhim, et al.
 Published: (2024-01-01)
- 
                
                    Low-Light Image Enhancement Using CycleGAN-Based Near-Infrared Image Generation and Fusion        
                          
 by: Min-Han Lee, et al.
 Published: (2024-12-01)
- 
                
                    Intestinal Polyp Segmentation Based on Histogram Equalization ResNet (PE-ResNet)        
                          
 by: Yukun AN, et al.
 Published: (2024-11-01)
- 
                
                    FI‐Net: Rethinking Feature Interactions for Medical Image Segmentation        
                          
 by: Yuhan Ding, et al.
 Published: (2024-12-01)
- 
                
                    SDRG-Net: Integrating multi-level color transformation encryption and ICNN-IRDO feature analysis for robust diabetic retinopathy diagnosis        
                          
 by: Venkata Kotam Raju Poranki, et al.
 Published: (2025-03-01)
 
       