Scanner-integrated reconstruction versus post-processing deep learning for low-count (18)F-FDG PET/CT: a comparative clinical evaluation.
- DOI
- 10.1186/s40658-026-00841-z
- Published
- 2026 Jan 31
- Container
- EJNMMI physics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1186/s40658-026-00841-z,
title = {Scanner-integrated reconstruction versus post-processing deep learning for low-count (18)F-FDG PET/CT: a comparative clinical evaluation.},
author = {Long Q and Tian Y and Hu Y and Xu Z and Zhang W and Xu S and Liu W and Jin J and Peng Y},
year = {2026},
journal = {EJNMMI physics},
doi = {10.1186/s40658-026-00841-z},
url = {https://doi.org/10.1186/s40658-026-00841-z}
}RIS
TY - JOUR TI - Scanner-integrated reconstruction versus post-processing deep learning for low-count (18)F-FDG PET/CT: a comparative clinical evaluation. AU - Long Q AU - Tian Y AU - Hu Y AU - Xu Z AU - Zhang W AU - Xu S AU - Liu W AU - Jin J AU - Peng Y PY - 2026 JO - EJNMMI physics DO - 10.1186/s40658-026-00841-z UR - https://doi.org/10.1186/s40658-026-00841-z ER -
APA
Q, L., Y, T., Y, H., Z, X., W, Z., S, X., W, L., J, J., & Y, P. (2026). Scanner-integrated reconstruction versus post-processing deep learning for low-count (18)F-FDG PET/CT: a comparative clinical evaluation.. EJNMMI physics. https://doi.org/10.1186/s40658-026-00841-z
Source records
- pubmed · retrieved 2026-09-26T18:24:14.545Z