Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-license: mit
+license:  cc-by-nc-nd-4.0
 task_categories:
   - image-segmentation
   - image-classification
@@ -38,13 +38,6 @@ This dataset was introduced in the ECCV 2024 paper: [FairDomain: Achieving Fairn
 | **Modalities**  | En-face fundus image, scanning laser ophthalmoscopy (SLO) fundus image |
 | **Samples**     | 10,000 (segmentation), 10,000 (classification) |
 | **Patients**    | 10,000 per task (unique patients) |
-| **License**     | CC BY-NC-ND 4.0 |
-
-- **Curated by:** Yu Tian, Congcong Wen, Min Shi, Muhammad Muneeb Afzal, Hao Huang, Muhammad Osama Khan, Yan Luo, Yi Fang, Mengyu Wang
-- **Language(s):** N/A (image data)
-- **License:** [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/)
-- **Repository:** [Harvard-Ophthalmology-AI-Lab/FairDomain](https://github.com/Harvard-Ophthalmology-AI-Lab/FairDomain)
-- **Paper:** [arXiv:2407.08813](https://arxiv.org/pdf/2407.08813)
 
 ### Source Data
 
@@ -65,16 +58,6 @@ Research on algorithmic fairness in cross-domain medical image segmentation and
 
 Clinical diagnosis, commercial applications, or any use prohibited by the CC BY-NC-ND 4.0 license.
 
-## Access
-
-The dataset can be downloaded via [Google Drive](https://drive.google.com/drive/folders/1huH93JVeXMj9rK6p1OZRub868vv0UK0O?usp=drive_link).
-
-If direct download is unavailable, request access via the Google Drive link. Access is typically granted within 3–5 business days.
-
-**Contact:** harvardophai@gmail.com, harvardairobotics@gmail.com
-
-> The "Harvard" designation indicates the dataset originates from the Department of Ophthalmology at Harvard Medical School. It does not imply endorsement, sponsorship, or legal responsibility by Harvard University or Harvard Medical School.
-
 ## Citation
 
 **BibTeX:**