Update README.md

README.md

@@ -1,3 +1,56 @@
----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+language:
+- en
+base_model:
+- YukunZhou/RETFound_dinov2_meh
+pipeline_tag: image-classification
+tags:
+- Indocyanine Green Angiography (ICGA)
+- binary classification
+- RETFound
+---
+# RETFound-DINOv2 (CNV_ICGA)
+
+Classification of Choroidal Neovascularization (CNV) on Indocyanine Green Angiography (ICGA) images.
+
+Binary classification: 1 (YES), 0 (NO)
+       
+This model is obtained by finetuning the pretrained model available in HuggingFace at this [link](https://huggingface.co/YukunZhou/RETFound_dinov2_meh).
+
+Trained on: [AngioReport](https://pubmed.ncbi.nlm.nih.gov/40610046/)
+
+## Usage
+
+Check instruction at the following [repository](https://gitlab.idiap.ch/medai/software/paper/fm-overspecialization)
+
+## Model output structure
+
+`[batch_size, num_classes]` (`num_classes=1`)
+
+## Related publication(s)
+
+```
+@article{xu_angioreport_2025,
+        title = {{AngioReport}: dataset and baseline methods for fundus angiography report generation},
+        issn = {0007-1161},
+        url = {https://bjo.bmj.com/content/early/2025/07/02/bjo-2024-327006},
+        doi = {10.1136/bjo-2024-327006},
+        journal = {British Journal of Ophthalmology},
+        author = {Xu, Pusheng and Chotcomwongse, Peranut and Zhang, Weiyi and Chen, Xiaolan and Wu, Xinyuan and Chung, Florence H T and Zhang, Xueli and He, Mingguang and Shi, Danli and Ruamviboonsuk, Paisan},
+        year = {2025},
+}
+@misc{he2021maskedautoencodersscalablevision,
+        title={Masked Autoencoders Are Scalable Vision Learners},
+        author={Kaiming He and Xinlei Chen and Saining Xie and Yanghao Li and Piotr Dollár and Ross Girshick},
+        year={2021},
+        eprint={2111.06377},
+        archivePrefix={arXiv},
+        primaryClass={cs.CV},
+        url={https://arxiv.org/abs/2111.06377},
+}
+```
+
+## Author(s)
+
+* Roberto Pulvirenti, Idiap Research Institute