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merge=lfs -text +# Audio files - compressed +*.aac filter=lfs diff=lfs merge=lfs -text +*.flac filter=lfs diff=lfs merge=lfs -text +*.mp3 filter=lfs diff=lfs merge=lfs -text +*.ogg filter=lfs diff=lfs merge=lfs -text +*.wav filter=lfs diff=lfs merge=lfs -text +# Image files - uncompressed +*.bmp filter=lfs diff=lfs merge=lfs -text +*.gif filter=lfs diff=lfs merge=lfs -text +*.png filter=lfs diff=lfs merge=lfs -text +*.tiff filter=lfs diff=lfs merge=lfs -text +# Image files - compressed +*.jpg filter=lfs diff=lfs merge=lfs -text +*.jpeg filter=lfs diff=lfs merge=lfs -text +*.webp filter=lfs diff=lfs merge=lfs -text +# Video files - compressed +*.mp4 filter=lfs diff=lfs merge=lfs -text +*.webm filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a501106bd264475b3a7ecf2ea3b6a2f4e02fce12 --- /dev/null +++ b/README.md @@ -0,0 +1,83 @@ +--- +license: cc-by-4.0 +task_categories: +- image-segmentation +- image-to-image +tags: +- medical +- neuroimaging +- stroke +- image-fusion +pretty_name: APIS Stroke Dataset (Lesion Cases Only) +size_categories: +- n<1K +--- + +# APIS Stroke Dataset - Preprocessed (Lesion Cases Only) + +This dataset contains **54 acute ischemic stroke cases** with expert lesion annotations from the APIS dataset. + +## Dataset Structure + +``` +preproc/ + train_000/ + ct.nii.gz # CT scan + mri.nii.gz # Registered MRI (ADC) + brain_mask.nii.gz # Brain ROI mask (TotalSegmentator) + bone_mask.nii.gz # Bone/skull ROI mask (TotalSegmentator) + lesion_mask.nii.gz # Expert-annotated lesion segmentation + train_001/ + ... + (54 cases total) + +splits/ + train.txt # 37 cases (68.5%) + val.txt # 8 cases (14.8%) + test.txt # 9 cases (16.7%) + split_metadata.json # Split statistics +``` + +## Excluded Cases + +6 cases without lesions were excluded: +- train_027, train_038, train_048, train_051, train_058, train_059 + +## Usage + +```python +from pathlib import Path +import nibabel as nib + +# Download dataset +from huggingface_hub import snapshot_download +data_dir = snapshot_download(repo_id="Pakawat-Phasook/ClinFuseDiff-APIS-Data", repo_type="dataset") + +# Load a case +case_dir = Path(data_dir) / "preproc" / "train_000" +ct = nib.load(case_dir / "ct.nii.gz") +mri = nib.load(case_dir / "mri.nii.gz") +lesion_mask = nib.load(case_dir / "lesion_mask.nii.gz") +``` + +## Citation + +```bibtex +@article{li2023apis, + title={APIS: A paired CT-MRI dataset with lesion labels for acute ischemic stroke}, + author={Li, Zongwei and others}, + journal={Scientific Data}, + year={2023} +} +``` + +## Preprocessing + +- **Registration**: MRI (ADC) registered to CT using ANTs SyN +- **ROI Masks**: Generated using TotalSegmentator v2 +- **Normalization**: CT windowed to brain (C=40, W=400 HU) +- **Format**: NIfTI (.nii.gz), isotropic 1mm spacing + +## License + +CC-BY-4.0 (original APIS dataset license) diff --git a/preproc/train_000/bone_mask.nii.gz 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file mode 100644 index 0000000000000000000000000000000000000000..77960fdec53bf67c346bda31da85ae87be369aa7 --- /dev/null +++ b/raw/README_DOWNLOAD_HERE.md @@ -0,0 +1,77 @@ +# 📥 APIS Dataset - Download Instructions + +**This directory is ready for your APIS dataset files.** + +--- + +## ✅ Expected Directory Structure + +Place your downloaded APIS dataset files in this structure: + +``` +raw/ +├── ct/ # ← CT volumes go here +│ ├── case_001/ +│ │ └── ct.nii.gz +│ ├── case_002/ +│ │ └── ct.nii.gz +│ └── ... (60 cases) +│ +├── adc/ # ← ADC/MRI volumes go here +│ ├── case_001/ +│ │ └── adc.nii.gz +│ ├── case_002/ +│ │ └── adc.nii.gz +│ └── ... (60 cases) +│ +└── lesion_masks/ # ← Lesion annotations go here + ├── case_001.nii.gz + ├── case_002.nii.gz + └── ... (60 files) +``` + +--- + +## 📋 Download Steps + +1. **Register**: Go to https://bivl2ab.uis.edu.co/challenges/apis +2. **Accept**: Accept the Data Usage Agreement +3. **Download**: Download CT, ADC/MRI, and lesion mask archives +4. **Extract**: Extract files into the directories above (ct/, adc/, lesion_masks/) + +--- + +## 🔍 Verify Download + +After extracting files, verify the structure: + +```powershell +wsl bash -c "cd /mnt/c/Users/User/Documents/ClinFuseDiff && bash workflow/02_verify_setup.sh" +``` + +This will check: +- ✅ Number of CT volumes found +- ✅ Number of ADC/MRI volumes found +- ✅ Number of lesion masks found +- ✅ File naming consistency + +--- + +## 🚀 Next Step + +Once verification passes, run the complete workflow: + +```powershell +wsl bash -c "cd /mnt/c/Users/User/Documents/ClinFuseDiff && source ~/miniconda3/etc/profile.d/conda.sh && conda activate clinfusediff && bash workflow/complete_workflow_with_logging.sh apis run_$(date +%Y%m%d_%H%M%S)" +``` + +This will automatically: +1. Preprocess all cases (ANTs registration + TotalSegmentator masks) +2. Create train/val/test splits +3. Train the model +4. Evaluate with comprehensive metrics +5. Save all outputs (logs, visualizations, checkpoints, results) + +--- + +**Ready to download? Visit the APIS challenge portal! 🚀** \ No newline at end of file diff --git a/raw/adc/train_000/adc.nii.gz b/raw/adc/train_000/adc.nii.gz new file mode 100644 index 0000000000000000000000000000000000000000..6ddc816fdd4262a25a84fd45910907c3d163dfc8 --- /dev/null +++ b/raw/adc/train_000/adc.nii.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:609ea15c519af6db9d37b48899cb0e9bfafab7eb6ca46bde8e1a851c9927b21f +size 2478282 diff --git a/raw/adc/train_001/adc.nii.gz b/raw/adc/train_001/adc.nii.gz new file mode 100644 index 0000000000000000000000000000000000000000..c393a809b76c2c7e9999caefa8e06528b14f7b02 --- /dev/null +++ b/raw/adc/train_001/adc.nii.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:806377a85d4d68d07f610fe135d19f3b64f3462d087b8b66db4afadae74a35a1 +size 468376 diff --git a/raw/adc/train_002/adc.nii.gz b/raw/adc/train_002/adc.nii.gz new file mode 100644 index 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