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.
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).
This repository hosts the pre-trained weights and datasets associated with the paper:
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.
1@article{zhao2026fundusegmenter,
2 author = {Zhao, Zhenyi and Mookiah, Muthu Rama Krishnan and Trucco, Emanuele},
3 title = {FunduSegmenter: Leveraging the RETFound Foundation Model for Joint Optic Disc and Optic Cup Segmentation in Retinal Fundus Images},
4 journal = {Translational Vision Science & Technology},
5 volume = {15},
6 number = {5},
7 pages = {14-14},
8 year = {2026},
9 month = {05}
10}
