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btcv

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Image Segmentation
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medical
CT
multi-organ
segmentation
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Live12 Angelou0516 commited on
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Duplicate from Angelou0516/btcv

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Co-authored-by: Ange Lou <Angelou0516@users.noreply.huggingface.co>

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  2. README.md +103 -0
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.gz filter=lfs diff=lfs merge=lfs -text
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+ *.h5 filter=lfs diff=lfs merge=lfs -text
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+ *.joblib filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.lz4 filter=lfs diff=lfs merge=lfs -text
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+ *.mds filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ *.safetensors filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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+ *.zst filter=lfs diff=lfs merge=lfs -text
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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - uncompressed
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README.md ADDED
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+ ---
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+ license: cc-by-4.0
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+ task_categories:
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+ - image-segmentation
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+ tags:
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+ - medical
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+ - CT
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+ - multi-organ
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+ - segmentation
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+ size_categories:
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+ - n<1K
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: train.jsonl
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+ ---
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+
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+ # Beyond the Cranial Vault Dataset
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+
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+ ## Dataset Description
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+
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+ The Beyond the Cranial Vault dataset for multi-organ abdominal CT segmentation. This dataset contains CT scans with dense segmentation annotations.
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+
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+ ### Dataset Details
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+
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+ - **Modality**: CT
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+ - **Target**: 13 abdominal organs
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+ - **Format**: NIfTI (.nii.gz)
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+
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+ ### Dataset Structure
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+
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+ Each sample in the JSONL file contains:
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+ ```json
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+ {
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+ "image": "path/to/image.nii.gz",
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+ "mask": "path/to/mask.nii.gz",
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+ "label": ["organ1", "organ2", ...],
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+ "modality": "CT",
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+ "dataset": "BTCV",
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+ "official_split": "train",
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+ "patient_id": "patient_id"
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+ }
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+ ```
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+
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+ ## Usage
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+
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+ ### Load Metadata
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load the dataset
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+ ds = load_dataset("Angelou0516/btcv")
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+
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+ # Access a sample
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+ sample = ds['train'][0]
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+ print(f"Patient ID: {sample['patient_id']}")
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+ print(f"Labels: {sample['label']}")
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+ ```
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+
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+ ### Load Images
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+
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+ ```python
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+ from huggingface_hub import snapshot_download
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+ import nibabel as nib
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+ import os
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+
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+ # Download the full dataset
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+ local_path = snapshot_download(
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+ repo_id="Angelou0516/btcv",
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+ repo_type="dataset"
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+ )
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+
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+ # Load a sample
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+ sample = ds['train'][0]
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+ image = nib.load(os.path.join(local_path, sample["image"]))
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+ mask = nib.load(os.path.join(local_path, sample['mask']))
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+
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+ # Get numpy arrays
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+ image_data = image.get_fdata()
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+ mask_data = mask.get_fdata()
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+
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+ print(f"Image shape: {image_data.shape}")
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+ print(f"Mask shape: {mask_data.shape}")
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+ ```
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @article{btcv,
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+ title={Multi-Atlas Labeling Beyond the Cranial Vault},
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+ year={2023}
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+ }
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+ ```
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+
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+ ## License
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+
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+ CC-BY-4.0
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+
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+ ## Dataset Homepage
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+
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+ https://www.synapse.org/#!Synapse:syn3193805
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