Upload APIS preprocessed dataset (lesion cases only, 54 cases)

README.md

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----
-license: mit
----
+---
+license: cc-by-4.0
+task_categories:
+- image-segmentation
+- image-to-image
+tags:
+- medical-imaging
+- stroke
+- mri
+- ct
+- image-fusion
+- diffusion
+size_categories:
+- n<100
+---
+
+# APIS Stroke Dataset - Preprocessed (Lesion Cases Only)
+
+## Dataset Description
+
+Preprocessed APIS (Acute ischemic stroke dataset from NIH) for multimodal medical image fusion research.
+**This version contains only cases with lesions (54/60 cases).**
+
+### Key Features
+
+- **54 cases** of acute ischemic stroke patients (6 no-lesion cases excluded)
+- **Paired CT-MRI scans** with expert lesion annotations
+- **ROI masks** generated with TotalSegmentator (brain + bone)
+- **Normalized** for deep learning (clinical windowing for CT, Z-score for MRI)
+- **Pre-registered** MRI to CT space using ANTs SyN
+
+### Files per Case
+
+```
+<case_id>/
+├── ct.nii.gz              # CT scan (clinical windowing: [-2, 2])
+├── mri_to_ct.nii.gz       # Registered MRI (Z-score: typically [-2, 5])
+├── brain_mask.nii.gz      # Brain ROI (TotalSegmentator)
+├── bone_mask.nii.gz       # Bone/skull ROI (TotalSegmentator)
+└── lesion_mask.nii.gz     # Expert-annotated lesion
+```
+
+## Dataset Statistics
+
+- **Total cases:** 54
+- **Excluded cases:** 6 (no lesions)
+- **Cases with lesions:** 54
+
+### Data Splits
+
+| Split | Count | Percentage |
+|-------|-------|------------|
+| Train | 37 | 68.5% |
+| Val   | 8 | 14.8% |
+| Test  | 9 | 16.7% |
+
+### Lesion Size Distribution
+
+- **Small (<5 mL):** 61.1% (majority)
+- **Medium (5-20 mL):** 16.7%
+- **Large (≥20 mL):** 22.2%
+- **Median volume:** 2.24 mL
+
+### Excluded Cases
+
+The following 6 cases were excluded (no lesion present):
+- train_027, train_038, train_048, train_051, train_058, train_059
+
+## Preprocessing Pipeline
+
+1. **TotalSegmentator**: Generate brain and bone ROI masks from CT
+2. **ANTs Registration**: Align MRI to CT space (SyN transformation)
+3. **CT Normalization**: Clinical windowing (Center=40 HU, Width=400 HU) → [-2, 2]
+4. **MRI Normalization**: Z-score normalization → typically [-2, 5]
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load dataset
+dataset = load_dataset("SuperAI/apis-stroke-preprocessed-lesion-only")
+
+# Access a case
+train_sample = dataset['train'][0]
+
+# Files are paths to .nii.gz volumes
+ct_path = train_sample['ct']
+mri_path = train_sample['mri_to_ct']
+brain_mask_path = train_sample['brain_mask']
+bone_mask_path = train_sample['bone_mask']
+lesion_mask_path = train_sample['lesion_mask']
+
+# Load with nibabel
+import nibabel as nib
+ct = nib.load(ct_path).get_fdata()
+```
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@misc{apis-stroke-preprocessed-2025,
+  title={APIS Stroke Dataset - Preprocessed for Image Fusion},
+  author={Phasook, Pakawat},
+  year={2025},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/datasets/SuperAI/apis-stroke-preprocessed-lesion-only}}
+}
+```
+
+Original APIS dataset:
+- **APIS Challenge**: https://www.api.sv/
+- **Paper**: To be announced by challenge organizers
+
+## License
+
+CC-BY-4.0 (following original APIS dataset license)
+
+## Intended Use
+
+This dataset is intended for:
+- Medical image fusion research
+- Multimodal learning
+- Stroke lesion segmentation
+- ROI-aware image synthesis
+
+**Not for clinical use.** This is a research dataset only.
+
+## Contact
+
+For questions or issues, please open an issue on the dataset repository.
+
+---
+
+**Preprocessed by:** CLIN-FuseDiff++ Pipeline (CVPR 2026)
+**Last updated:** 2025-10-23

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