End-to-end deep learning pipeline for automated IMRT planning in lymphoma: Feasibility and limitations.

Kutnár D, Vogelius IR, Georgiev HA, Håkansson KE, Specht L, Petersen J

DOI: 10.1002/acm2.70702
Published: 2026 Aug
Container: Journal of applied clinical medical physics
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1002/acm2.70702,
  title = {End-to-end deep learning pipeline for automated IMRT planning in lymphoma: Feasibility and limitations.},
  author = {Kutnár D and Vogelius IR and Georgiev HA and Håkansson KE and Specht L and Petersen J},
  year = {2026},
  journal = {Journal of applied clinical medical physics},
  doi = {10.1002/acm2.70702},
  url = {https://doi.org/10.1002/acm2.70702}
}

RIS

TY  - JOUR
TI  - End-to-end deep learning pipeline for automated IMRT planning in lymphoma: Feasibility and limitations.
AU  - Kutnár D
AU  - Vogelius IR
AU  - Georgiev HA
AU  - Håkansson KE
AU  - Specht L
AU  - Petersen J
PY  - 2026
JO  - Journal of applied clinical medical physics
DO  - 10.1002/acm2.70702
UR  - https://doi.org/10.1002/acm2.70702
ER  -

APA

D, K., IR, V., HA, G., KE, H., L, S., & J, P. (2026). End-to-end deep learning pipeline for automated IMRT planning in lymphoma: Feasibility and limitations.. Journal of applied clinical medical physics. https://doi.org/10.1002/acm2.70702

Source records

pubmed · retrieved 2026-11-10T07:33:35.898Z