RetNet-10: A Lightweight Deep Learning Model for Diabetic Retinopathy Image Classification

📚 This repository contains the original implementation of RetNet-10 for classifying a wide range of Diabetic Retinopathy Images.

📧 Contact: For inquiries, you can reach out to us at m.raiaan.cs@gmail.com.

Paper

📄 This code implements the paper published in a Q1 Journal, IEEE Access, with an impact factor of 3.47 and an H-INDEX of 204:

Title: A Lightweight Robust Deep Learning Model Gained High Accuracy in Classifying a Wide Range of Diabetic Retinopathy Images

Authors: Mohaimenul Azam Khan Raiaan, Kaniz Fatema, Inam Ullah Khan, Sami Azam, Md. Rafi Ur Rashid, Md. Saddam Hossain Mukta, Mirjam Jonkman, Friso De Boer

Year: 2023

DOI: 10.1109/ACCESS.2023.3272228

Dataset Availability

This project uses the following datasets for Diabetic Retinopathy Images:

• APTOS Dataset
• Messidor-2 Dataset
• IDRiD Dataset

Code

You can find the implementation of RetNet-10 in the following file:

• RetNet-10 Model.py

Model Architecture

Citation Request

If you find this work helpful for your research, please consider citing our paper:

• Cite:

  @ARTICLE{10113630,
    author={Raiaan, Mohaimenul Azam Khan and Fatema, Kaniz and Khan, Inam Ullah and Azam, Sami and Rashid, Md. Rafi Ur and Mukta, Md. Saddam Hossain and Jonkman, Mirjam and De Boer, Friso},
    journal={IEEE Access},
    title={A Lightweight Robust Deep Learning Model Gained High Accuracy in Classifying a Wide Range of Diabetic Retinopathy Images},
    year={2023},
    volume={11},
    number={},
    pages={42361-42388},
    doi={10.1109/ACCESS.2023.3272228}
  }

Copying

This code is shared for research use only. If you encounter any issues or find inappropriate content in this code, please feel free to contact us.

License

This project is licensed under a Creative Commons License.