FunduSegmenter

--- license: cc-by-nc-4.0 pipeline_tag: image-segmentation library_name: pytorch tags: - medical-imaging - foundation models - fine-tuning - retina - fundus - optic disc - optic cup - domain generalization --- # 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://doi.org/10.1167/tvst.15.5.14) - **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{zhao...

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