NFDI4BIOIMAGE
Published April 10, 2024 | Version v2
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Insights from Acquiring Open Medical Imaging Datasets for Foundation Model Development

Creators

Contributors

  • 1. ROR icon German BioImaging – Gesellschaft für Mikroskopie und Bildanalyse
  • 2. ROR icon German Cancer Research Center
  • 3. Helmholtz Imaging
  • 4. Helmholtz Metadata Collaboration (HMC) Hub Health
  • 5. ROR icon University Hospital Heidelberg

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InsightsClinicalImgFM_Talk_Munich_10.04.2024.pptx (2).pdf

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Additional details

References
Publication: 10.1038/s41592-020-01008-z (DOI)
Other: https://www.maximedturkey.com/de/blog/ct-scan-vs-mri-what-s-the-difference (URL)
Drawing: https://www.freepik.com/photos/world (URL)
Image: https://medium.com/vsinghbisen/what-is-medical-image-annotation-role-in-ai-medical-diagnostics-a44338bb9bdb (URL)
Other: https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access (URL)
Diagram: https://specs.fairdatapoint.org/fdp-specs-v1.2.html (URL)
Image: https://www.european-health-data-space.com/ (URL)
Image: https://racoon.network/ (URL)
Image: https://www.medizininformatik-initiative.de/de/start (URL)
Image: https://cancerimage.eu/ (URL)

References

  • Isensee, Fabian, et al. "nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation." Nature methods 18.2 (2021): 203-211.