Toward reproducible metabolic tumor volume quantification in endometrial cancer: optimizing [¹⁸F]FDG PET/CT tumor segmentation methods
- DOI
- 10.1186/s13550-026-01412-0
- Published
- 2026-05-28
- Container
- EJNMMI Research
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s13550-026-01412-0,
title = {Toward reproducible metabolic tumor volume quantification in endometrial cancer: optimizing [¹⁸F]FDG PET/CT tumor segmentation methods},
author = {Kristine Eldevik Fasmer and Sunniva Lindås and Ankush Gulati and Julie Andrea Dybvik and Erlend Hodneland and Camilla Krakstad and Ingfrid Salvesen Haldorsen},
year = {2026},
journal = {EJNMMI Research},
doi = {10.1186/s13550-026-01412-0},
url = {https://doi.org/10.1186/s13550-026-01412-0}
}RIS
TY - JOUR TI - Toward reproducible metabolic tumor volume quantification in endometrial cancer: optimizing [¹⁸F]FDG PET/CT tumor segmentation methods AU - Kristine Eldevik Fasmer AU - Sunniva Lindås AU - Ankush Gulati AU - Julie Andrea Dybvik AU - Erlend Hodneland AU - Camilla Krakstad AU - Ingfrid Salvesen Haldorsen PY - 2026 JO - EJNMMI Research DO - 10.1186/s13550-026-01412-0 UR - https://doi.org/10.1186/s13550-026-01412-0 ER -
APA
Fasmer, K. E., Lindås, S., Gulati, A., Dybvik, J. A., Hodneland, E., Krakstad, C., & Haldorsen, I. S. (2026). Toward reproducible metabolic tumor volume quantification in endometrial cancer: optimizing [¹⁸F]FDG PET/CT tumor segmentation methods. EJNMMI Research. https://doi.org/10.1186/s13550-026-01412-0
Source records
- crossref · retrieved 2026-11-06T21:49:20.732Z