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
2) h5py: https://www.h5py.org
3) pymicro: https://github.com/heprom/pymicro
Trained models to segment this dataset: 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},
}
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