license: cc-by-nc-4.0
pipeline_tag: image-segmentation
library_name: pytorch
tags:
- medical
- retina
- fundus
- medical-imaging
FunduSegmenter
This is the official repository for FunduSegmenter, the first adaptation of the RETFound foundation model for joint optic disc (OD) and optic cup (OC) segmentation in retinal fundus images.
- Paper: FunduSegmenter: Leveraging the RETFound Foundation Model for Joint Optic Disc and Optic Cup Segmentation in Retinal Fundus Images
- Code: GitHub - JusticeZzy/FunduSegmenter
- License: CC BY-NC 4.0 (Non-commercial use only)
Introduction
FunduSegmenter integrates a series of novel modules with RETFound, including a Pre-adapter, a Decoder, a Post-adapter, skip connections with Convolutional Block Attention Module (CBAM), and a Vision Transformer block adapter. The model demonstrates strong stability and generalization on both in-distribution and out-of-distribution data, providing stable OD and OC segmentation across multiple fundus camera datasets (IDRiD, Drishti-GS, RIM-ONE-r3, and REFUGE).
Repository Contents
This repository hosts the pre-trained weights and datasets associated with the paper:
- Datasets.zip: Processed datasets used in the study.
- DUNet_OD_CentreCrop_pretrained.pth: Pre-trained DUNet used for OD center cropping pre-processing.
- FunduSegmenter_CroppedImage.pth: Pre-trained FunduSegmenter trained on cropped ROI images.
- FunduSegmenter_OriginalImage.pth: Pre-trained FunduSegmenter trained on original fundus images.
- Weights.zip: All trained weights reported in the paper's experiments.
- mobilenet_v2-6a65762b.pth: Required pre-trained weight for the DoFE baseline.
License Note
While the code in the GitHub repository is under the MIT License, all the weights (including the original RETFound weights and the derived FunduSegmenter weights) are under CC BY-NC 4.0 (Creative Commons Attribution-NonCommercial 4.0 International). This means the weights are for non-commercial use only.
Citation
If you use our code or weights, please cite the following paper:
@article{zhao2025fundusegmenter,
title={FunduSegmenter: Leveraging the RETFound Foundation Model for Joint Optic Disc and Optic Cup Segmentation in Retinal Fundus Images},
author={Zhao, Zhenyi and Mookiah, M R K and Trucco, Emanuele},
journal={arXiv preprint arXiv:2508.11354},
year={2025}
}
Contact
Zhenyi Zhao: zhenyi.zhao@hotmail.com or 2578745@dundee.ac.uk