| --- |
| 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](https://github.com/rmaphoh/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](https://huggingface.co/papers/2508.11354) |
| - **Code:** [GitHub - JusticeZzy/FunduSegmenter](https://github.com/JusticeZzy/FunduSegmenter) |
| - **License:** [CC BY-NC 4.0](https://creativecommons.org/licenses/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: |
|
|
| 1. **Datasets.zip**: Processed datasets used in the study. |
| 2. **DUNet_OD_CentreCrop_pretrained.pth**: Pre-trained DUNet used for OD center cropping pre-processing. |
| 3. **FunduSegmenter_CroppedImage.pth**: Pre-trained FunduSegmenter trained on cropped ROI images. |
| 4. **FunduSegmenter_OriginalImage.pth**: Pre-trained FunduSegmenter trained on original fundus images. |
| 5. **Weights.zip**: All trained weights reported in the paper's experiments. |
| 6. **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: |
|
|
| ```bibtex |
| @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 |
