Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,109 @@
+---
+license: cc-by-4.0
+task_categories:
+- image-segmentation
+tags:
+- medical
+- CT
+- segmentation
+- WORD
+size_categories:
+- n<1K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: train.jsonl
+  - split: test
+    path: test.jsonl
+  - split: validation
+    path: validation.jsonl
+---
+
+# WORD (Whole abdominal ORgan Dataset) Dataset
+
+## Dataset Description
+
+The WORD (Whole abdominal ORgan Dataset) dataset for abdominal organ segmentation with 16 organs. This dataset contains CT scans with dense segmentation annotations.
+
+### Dataset Details
+
+- **Modality**: CT
+- **Target**: liver, spleen, kidneys, stomach, gallbladder, esophagus, pancreas, duodenum, colon, intestine, adrenal gland, rectum, bladder, femoral heads
+- **Format**: NIfTI (.nii.gz)
+
+### Dataset Structure
+
+Each sample in the JSONL file contains:
+```json
+{
+  "image": "path/to/image.nii.gz",
+  "mask": "path/to/mask.nii.gz",
+  "label": ["organ1", "organ2", ...],
+  "modality": "CT",
+  "dataset": "WORD",
+  "official_split": "train",
+  "patient_id": "patient_id"
+}
+```
+
+## Usage
+
+### Load Metadata
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+ds = load_dataset("Angelou0516/word")
+
+# Access a sample
+sample = ds['train'][0]
+print(f"Patient ID: {sample['patient_id']}")
+print(f"Image: {sample['image']}")
+print(f"Mask: {sample['mask']}")
+print(f"Labels: {sample['label']}")
+```
+
+### Load Images
+
+```python
+from huggingface_hub import snapshot_download
+import nibabel as nib
+import os
+
+# Download the full dataset
+local_path = snapshot_download(
+    repo_id="Angelou0516/word",
+    repo_type="dataset"
+)
+
+# Load a sample
+sample = ds['train'][0]
+image = nib.load(os.path.join(local_path, sample['image']))
+mask = nib.load(os.path.join(local_path, sample['mask']))
+
+# Get numpy arrays
+image_data = image.get_fdata()
+mask_data = mask.get_fdata()
+
+print(f"Image shape: {image_data.shape}")
+print(f"Mask shape: {mask_data.shape}")
+```
+
+## Citation
+
+```bibtex
+@article{word,
+  title={WORD: A Large Scale Dataset for Whole Abdominal Organ Segmentation},
+  year={2023}
+}
+```
+
+## License
+
+CC-BY-4.0
+
+## Dataset Homepage
+
+https://github.com/HiLab-git/WORD