RadField3D: a data generator and data format for deep learning in radiation-protection dosimetry for medical applications.

Lehner F, Lombardo P, Castillo S, Hupe O, Magnor M

DOI: 10.1088/1361-6498/add53d
Published: 2025 May 16
Container: Journal of radiological protection : official journal of the Society for Radiological Protection
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1088/1361-6498/add53d,
  title = {RadField3D: a data generator and data format for deep learning in radiation-protection dosimetry for medical applications.},
  author = {Lehner F and Lombardo P and Castillo S and Hupe O and Magnor M},
  year = {2025},
  journal = {Journal of radiological protection : official journal of the Society for Radiological Protection},
  doi = {10.1088/1361-6498/add53d},
  url = {https://doi.org/10.1088/1361-6498/add53d}
}

RIS

TY  - JOUR
TI  - RadField3D: a data generator and data format for deep learning in radiation-protection dosimetry for medical applications.
AU  - Lehner F
AU  - Lombardo P
AU  - Castillo S
AU  - Hupe O
AU  - Magnor M
PY  - 2025
JO  - Journal of radiological protection : official journal of the Society for Radiological Protection
DO  - 10.1088/1361-6498/add53d
UR  - https://doi.org/10.1088/1361-6498/add53d
ER  -

APA

F, L., P, L., S, C., O, H., & M, M. (2025). RadField3D: a data generator and data format for deep learning in radiation-protection dosimetry for medical applications.. Journal of radiological protection : official journal of the Society for Radiological Protection. https://doi.org/10.1088/1361-6498/add53d

Source records

pubmed · retrieved 2026-09-25T08:46:23.468Z