Update README.md

README.md

@@ -1,4 +1,34 @@
 ---
+annotations_creators:
+- machine-generated
+language:
+- en
+license: cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: OpenMind2D
+size_categories:
+- 100K<n<1M
+source_datasets:
+- AnonRes/OpenMind
+task_categories:
+- image-classification
+- image-to-text
+- zero-shot-image-classification
+task_ids:
+- medical-image-analysis
+- brain-mri-analysis
+- neuroimaging
+- self-supervised-learning
+tags:
+- medical
+- neuroimaging
+- brain
+- mri
+- 3d-to-2d
+- computer-vision
+- healthcare
+paperswithcode_id: openmind
 dataset_info:
   features:
   - name: image
@@ -43,13 +73,95 @@ dataset_info:
     dtype: int32
   splits:
   - name: train
-    num_bytes: 3877372385.478
+    num_bytes: 16787700000
     num_examples: 335754
-  download_size: 3965343677
-  dataset_size: 3877372385.478
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+  download_size: 11751390000
+  dataset_size: 16787700000
 ---
+
+# OpenMind2D: 2D Brain MRI Slices
+
+OpenMind2D is a 2D medical imaging dataset derived from the [OpenMind dataset](https://huggingface.co/datasets/AnonRes/OpenMind). It contains 335,754 2D slices extracted from 3D brain MRI volumes in three anatomical orientations (axial, sagittal, coronal).
+
+## Dataset Statistics
+
+- **Total Images**: 335,754
+- **Resolution**: 256×256 pixels
+- **Format**: JPEG
+- **Size**: ~11.7 GB
+- **Splits**: Train (70%), Validation (20%), Test (10%)
+- **Orientations**: Axial, sagittal, coronal
+- **Modalities**: T1w, T2w, FLAIR, DWI, and 19+ additional MRI types
+
+## Source
+
+This dataset is derived from the OpenMind dataset ([Dufumier et al., 2024](https://arxiv.org/abs/2412.17041)), which contains 114,000 3D brain MRI volumes from 800 OpenNeuro datasets.
+
+### Processing
+
+1. Slice extraction from three anatomical orientations
+2. Isotropic resampling to 1mm³ spacing
+3. Intensity normalization (1st-99th percentile clipping)
+4. Resize to 256×256 pixels
+5. JPEG compression with metadata preservation
+
+## Dataset Structure
+
+```
+OpenMind2D/
+├── metadata.parquet    # Primary metadata
+├── train/             # All images
+│   ├── 00000001_000.jpg
+│   └── ...
+└── README.md
+```
+
+### Key Metadata Fields
+
+- `image`: 256×256 JPEG brain MRI slice
+- `orientation`: axial, sagittal, or coronal
+- `volume_id`: Volume identifier
+- `unique_id`: Original OpenMind volume ID
+- `modality`: MRI sequence type
+- `split`: train/validation/test
+- `age`: Subject age
+- `sex`: Subject sex
+- `manufacturer`: Scanner manufacturer
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load dataset
+dataset = load_dataset("liamchalcroft/OpenMind2D")
+train_data = dataset['train']
+
+# Get sample
+sample = train_data[0]
+image = sample['image']
+orientation = sample['orientation']
+modality = sample['modality']
+
+# Filter by modality or orientation
+t1_data = dataset.filter(lambda x: x['modality'] == 'T1w')
+axial_data = dataset.filter(lambda x: x['orientation'] == 'axial')
+```
+
+## Citation
+
+If you use this dataset, please cite the original OpenMind work:
+
+```bibtex
+@article{dufumier2024openmind,
+  title = {OpenMind: A Large-Scale Dataset for Self-Supervised Learning in Medical Imaging},
+  author = {Dufumier, Basile and others},
+  journal = {arXiv preprint arXiv:2412.17041},
+  year = {2024},
+  url = {https://arxiv.org/abs/2412.17041}
+}
+```
+
+## License
+
+This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0), consistent with the original OpenMind dataset.