Omkar2118/datasets huggingface dataset:
GF-PA66 3D XCT (latest)
Full name: Glass fiber-reinforced polyamide 66 3D X-ray Computed Tomography

Stack of 2D gray images of glass fiber-reinforced polyamide 66 (GF-PA66) 3D X-ray Computed Tomography (XCT) specimen.

Usage: 2D/3D image segmentation
Format: HDF5

Libraries to read HDF5 files:

1) silx: [https://github.com/silx-kit/silx](https://github.com/silx-kit/silx)

2) h5py: [https://www.h5py.org](https://www.h5py.org)

3) pymicro: [https://github.com/heprom/pymicro](https://github.com/heprom/pymicro)

Trained models to segment this dataset: [https://doi.org/10.5281/zenodo.4601560](https://doi.org/10.5281/zenodo.4601560)

Please cite us as

```
@ARTICLE{10.3389/fmats.2021.761229,
    AUTHOR={Bertoldo, João P. C. and Decencière, Etienne and Ryckelynck, David and Proudhon, Henry},
    TITLE={A Modular U-Net for Automated Segmentation of X-Ray Tomography Images in Composite Materials},
    JOURNAL={Frontiers in Materials},
    VOLUME={8},
    YEAR={2021},
    URL={https://www.frontiersin.org/article/10.3389/fmats.2021.761229},
    DOI={10.3389/fmats.2021.761229},
    ISSN={2296-8016},
}
```

Introducing paper: A modular U-Net for automated segmentation of X-ray tomography images in composite materials