Publication: Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney
Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney
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Kuo, W., Rossinelli, D., Schulz, G., Wenger, R. H., Hieber, S., Müller, B., & Kurtcuoglu, V. (2023). Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney. Scientific Data, 10, 510. https://doi.org/10.1038/s41597-023-02407-5
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The performance of machine learning algorithms, when used for segmenting 3D biomedical images, does not reach the level expected based on results achieved with 2D photos. This may be explained by the comparative lack of high-volume, high-quality training datasets, which require state-of-the-art imaging facilities, domain experts for annotation and large computational and personal resources. The HR-Kidney dataset presented in this work bridges this gap by providing 1.7 TB of artefact-corrected synchrotron radiation-based X-ray phase-co
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- Rossinelli, Diego
- Schulz, Georg
- Wenger, Roland H
- Hieber, Simone
- Müller, Bert
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Kuo, W., Rossinelli, D., Schulz, G., Wenger, R. H., Hieber, S., Müller, B., & Kurtcuoglu, V. (2023). Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney. Scientific Data, 10, 510. https://doi.org/10.1038/s41597-023-02407-5
