Update README.md

README.md

@@ -1,11 +1,11 @@
-# MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation towards Unannotated Modalities
+# MRGen: Segmentation Data Engine For Underrepresented MRI Modalities
 This repository contains the curated MedGen-1M dataset proposed in MRGen: https://arxiv.org/abs/2412.04106/.
 
 ## Some Information
-[Project Page](https://haoningwu3639.github.io/MRGen/) $\cdot$ [Paper](https://arxiv.org/abs/2412.04106/) $\cdot$ [Dataset](https://huggingface.co/datasets/haoningwu/MedGen-1M) $\cdot$ [Checkpoints](https://huggingface.co/haoningwu/MRGen)
+[Project Page](https://haoningwu3639.github.io/MRGen/) $\cdot$ [Paper](https://arxiv.org/abs/2412.04106/) $\cdot$ [Dataset](https://huggingface.co/datasets/haoningwu/MRGen-DB) $\cdot$ [Checkpoints](https://huggingface.co/haoningwu/MRGen)
 
 ## Dataset
-Please check out [MedGen-1M](https://huggingface.co/datasets/haoningwu/MedGen-1M) to download our curated dataset, including two parts: `radiopaedia_data` and `conditional_dataset`.
+Please check out [MRGen-DB](https://huggingface.co/datasets/haoningwu/MRGen-DB) to download our curated dataset, including two parts: `radiopaedia_data` and `conditional_dataset`.
 
 For the conditional dataset, we have directly provided our processed data, including the raw image, mask annotations, and text descriptions.
 
@@ -13,14 +13,14 @@ As described in our paper, considering the data privacy concerns of [Radiopaedia
 For each case, the format is represented as `./radiopaedia/{patient_id}/{case_id}/{volume_id}/{slice_id}.jpeg`, for example, `./radiopaedia/2564/1/MRI_4/1.jpeg`.
 This format allows you to locate the corresponding original volume through the `link` provided in our json files. 
 After obtaining official authorization from Radiopaedia, you may download the data corresponding to the JSON file on your own. 
-Alternatively, you can send the authorization via email to us (`[email protected]` or `[email protected]`) to obtain the download link for the image data in our MedGen-1M.
+Alternatively, you can send the authorization via email to us (`[email protected]` or `[email protected]`) to obtain the download link for the image data in our MRGen-DB.
 
 ## Citation
 If you use this dataset for your research or project, please cite:
 
 	@misc{wu2024mrgen,
             author  = {Wu, Haoning and Zhao, Ziheng and Zhang, Ya and Xie, Weidi and Wang, Yanfeng},
-            title   = {MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation towards Unannotated Modalities},
+            title   = {MRGen: Segmentation Data Engine For Underrepresented MRI Modalities},
             journal = {arXiv preprint arXiv:2412.04106},
             year    = {2024},
       }