Deep learning model using planar whole-body bone scintigraphy for diagnosis of skull base invasion in patients with nasopharyngeal carcinoma
Deep learning models utilizing partial-body input from planar whole-body bone scintigraphy demonstrate high discriminatory power for diagnosing SBI in NPC patients, surpassing experienced nuclear medicine physicians.
Authors
- Shulin Song
- Wei Fu (ORCID: https://orcid.org/0009-0004-6087-6183)
- Xingyu Mu (ORCID: https://orcid.org/0000-0002-8459-4541)
- Guanqiao Jin (ORCID: https://orcid.org/0000-0003-2142-9001)
- Lijuan Liu (ORCID: https://orcid.org/0000-0002-8326-0371)
- Ting Li (ORCID: https://orcid.org/0009-0009-2967-3237)
- Zhao Ge (ORCID: https://orcid.org/0009-0001-0067-975X)
- Denglu Lu
- Cheng Chen (ORCID: https://orcid.org/0009-0001-6411-0394)
Institutions
- Guangxi Medical University (CN)
- Guilin Medical University (CN)
- The Fourth People's Hospital (CN)
- Fourth Affiliated Hospital of Guangxi Medical University (CN)
Publication Details
- Journal
- Journal of Cancer Research and Clinical Oncology
- Published
- 2024-10-09
- DOI
- https://doi.org/10.1007/s00432-024-05969-y
- Citations
- 5
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.90
Funders
- Guangxi Zhuang Autonomous Region Health and Family Planning Commission
- Guangxi Key Research and Development Program