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README.md

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+# STimage-1K4M Dataset
+
+Welcome to the STimage-1K4M Dataset repository. This dataset is designed to foster research in the field of spatial transcriptomics, combining high-resolution histopathology images with detailed gene expression data. 
+
+![teaser](aux/f1.png "teaser")
+
+
+## Dataset Description
+
+STimage-1K4M consists of 1,149 spatial transcriptomics slides, totaling over 4 million spots with paired gene expression data. This dataset includes:
+
+- Images.
+- Gene expression profiles matched with high-resolution histopathology images.
+- Spatial coordinates for each spot.
+
+## Data structure
+The data structure is organized as follows:
+
+```bash
+├── annotation              # Pathologist annotation
+├── meta                    # Test files (alternatively `spec` or `tests`)
+│   ├── bib.txt             # the bibtex for all studies with pmid included in the dataset
+│   ├── meta_all_gene.csv   # The meta information
+├── ST                      # Include all data for tech: Spatial Transcriptomics
+│   ├── coord               # Include the spot coordinates & spot radius of each slide
+│   ├── gene_exp            # Include the gene expression of each slide
+│   └── image               # Include the image each slide
+├── Visium                  # Include all data for tech: Visium, same structure as ST
+├── VisiumHD                # Include all data for tech: VisiumHD, same structure as ST
+```
+## Repository structure
+
+The code for data processing and reproducing evaluation result in the paper are in [Document](https://jiawenchenn.github.io/STimage-1K4M/docs/01-make-meta).
+
+## Acknowledgement
+The fine-tuning and evaluation codes borrows heavily from [CLIP](https://github.com/openai/CLIP/issues/83) and [PLIP](https://github.com/PathologyFoundation/plip/). 
+
+## Citation
+
+```
+@misc{chen2024stimage1k4m,
+      title={STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics}, 
+      author={Jiawen Chen and Muqing Zhou and Wenrong Wu and Jinwei Zhang and Yun Li and Didong Li},
+      year={2024},
+      eprint={2406.06393},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```
+
+## License
+
+All code is licensed under the MIT License - see the LICENSE.md file for details.