MedFuse: a multi-source data fusion framework for diabetic retinopathy lesion segmentation

Graphical abstract

References

[1] Guo F, Yang S, Ge R, Li W, Lu A, Feng R, Fang W, Jin Q. . RetinaDA: a diverse dataset for domain adaptation in retinal vessel segmentation. Frontiers of Computer Science, 2025, 19( 8): 198917

[2] Luo X, Xu Q, Wu H, Liu C, Lai Z, Shen L. Like an ophthalmologist: dynamic selection driven multi-view learning for diabetic retinopathy grading. In: Proceedings of the 39th AAAI Conference on Artificial Intelligence. 2025, 19224–19232

[3] Yang Q, Ma B, Cui H, Ma J. AMF-NET: attention-aware multi-scale fusion network for retinal vessel segmentation. In: Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society. 2021, 3277–3280

[4] Li X, Wu X. WSRFNet: wavelet-based scale-specific recurrent feedback network for diabetic retinopathy lesion segmentation. In: Proceedings of the 33rd International Joint Conference on Artificial Intelligence. 2024, 1038–1046

[5] Liu Z, Lin Y, Cao Y, Hu H, Wei Y, Zhang Z, Lin S, Guo B. Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of 2021 IEEE/CVF International Conference on Computer Vision. 2021, 10012–10022

[6] MMSegmentation Contributors. MMSegmentation: OpenMMLab semantic segmentation toolbox and benchmark. See gitee.com/deadkany/mmsegmentation website, 2020

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Higher Education Press