Datasets:
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license: cc-by-nc-4.0
pretty_name: OrganMNIST3D Subset (Bladder and Femur-Right)
task_categories:
- image-classification
tags:
- biomedical-imaging
- 3d
- NIfTI file format (.nii.gz)
- medmnist+
- autoencodix
---
# Info
Subset of the MedMNIST+ OrganMNIST3D dataset containing only the organ classes bladder and femur-right, prepared for use with the [AUTOENCODIX ](https://github.com/jan-forest/autoencodix_package) Imagix3D tutorial. The complete MedMNIST dataset collections can be found [here](https://medmnist.com/).
OrganMNIST3D is a three-dimensional biomedical image classification dataset derived from abdominal CT scans. The MedMNIST+ version provides the volumes at a spatial resolution of 64 × 64 × 64 voxels.
For this tutorial dataset, only samples belonging to the bladder and right-femur classes were retained. The volumes were converted from its original .npz file format to compressed NIfTI files (.nii.gz).
# Contents
- 345 images (174 bladder, 171 femur-right) with a spatial size of 64 × 64 × 64 voxels.
- organmnist3d_images.zip: compressed archive containing the individual volumes in NIfTI format (.nii.gz).
- organmnist3d_mappings.csv: comma-separated annotation file containing the sample identifiers, paths to the corresponding NIfTI files, and organ-class labels.
# Loading
The files can be downloaded from Hugging Face using huggingface_hub:
```python
from huggingface_hub import hf_hub_download
import zipfile
mapping_path = hf_hub_download(
repo_id="autoencodix/OrganMNIST3D-subsample",
repo_type="dataset",
filename="organmnist3d_mappings.csv",
)
zip_path = hf_hub_download(
repo_id="autoencodix/OrganMNIST3D-subsample",
repo_type="dataset",
filename="organmnist3d_images.zip",
)
with zipfile.ZipFile(zip_path) as zf:
zf.extractall("data/images/")
```
# License
Original dataset licensed under [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/), see: https://medmnist.com/.
The [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0) license associated with the MedMNIST project applies to the MedMNIST software code, see: https://github.com/MedMNIST/MedMNIST/.
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