Torso synthetic CT generation by integrating deep learning and segmentation for FDG-PET/MR attenuation correction
- DOI
- 10.1088/2057-1976/ae13ff
- Published
- 2025-11-06
- Container
- Biomedical Physics & Engineering Express
- Publisher
- IOP Publishing
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1088/2057-1976/ae13ff,
title = {Torso synthetic CT generation by integrating deep learning and segmentation for FDG-PET/MR attenuation correction},
author = {Jin Uk Heo and Shujin Sun and Robert S Jones and Yi Gu and Yizhang Jiang and Pengjiang Qian and Atallah Baydoun and Theodore Higgins Arsenault and Melanie Traughber and Rose Al Helo and Cheryl Thompson and Min Yao and Jennifer Dorth and John Nakayama and Steven E Waggoner and Tithi Biswas and Eleanor Harris and S Kate Sandstrom and Bryan J Traughber and Raymond F Muzic},
year = {2025},
journal = {Biomedical Physics \& Engineering Express},
doi = {10.1088/2057-1976/ae13ff},
url = {https://doi.org/10.1088/2057-1976/ae13ff}
}RIS
TY - JOUR TI - Torso synthetic CT generation by integrating deep learning and segmentation for FDG-PET/MR attenuation correction AU - Jin Uk Heo AU - Shujin Sun AU - Robert S Jones AU - Yi Gu AU - Yizhang Jiang AU - Pengjiang Qian AU - Atallah Baydoun AU - Theodore Higgins Arsenault AU - Melanie Traughber AU - Rose Al Helo AU - Cheryl Thompson AU - Min Yao AU - Jennifer Dorth AU - John Nakayama AU - Steven E Waggoner AU - Tithi Biswas AU - Eleanor Harris AU - S Kate Sandstrom AU - Bryan J Traughber AU - Raymond F Muzic PY - 2025 JO - Biomedical Physics & Engineering Express DO - 10.1088/2057-1976/ae13ff UR - https://doi.org/10.1088/2057-1976/ae13ff ER -
APA
Heo, J. U., Sun, S., Jones, R. S., Gu, Y., Jiang, Y., Qian, P., Baydoun, A., Arsenault, T. H., Traughber, M., Helo, R. A., Thompson, C., Yao, M., Dorth, J., Nakayama, J., Waggoner, S. E., Biswas, T., Harris, E., Sandstrom, S. K., Traughber, B. J., & Muzic, R. F. (2025). Torso synthetic CT generation by integrating deep learning and segmentation for FDG-PET/MR attenuation correction. Biomedical Physics & Engineering Express. https://doi.org/10.1088/2057-1976/ae13ff
Source records
- crossref · retrieved 2026-09-26T23:35:45.236Z