Assessment of prostate cancer aggressiveness through the combined analysis of prostate MRI and 2.5D deep learning models
Our 2.5D deep learning model based on prostate MRI showed efficacy in identifying clinically significant prostate cancer, providing valuable references for clinical treatment and enhancing patient net benefit.
Authors
- Y. Yuan (ORCID: https://orcid.org/0000-0002-6860-8966)
- Bao‐Qi Zhang (ORCID: https://orcid.org/0009-0007-0623-6371)
- Bo Guan
- Fuqiang Pan
- Manman Zhang (ORCID: https://orcid.org/0000-0002-1095-0806)
- Yang Zhang (ORCID: https://orcid.org/0000-0002-9878-6368)
- Li Xu (ORCID: https://orcid.org/0000-0003-2721-0377)
- Lei Zhang (ORCID: https://orcid.org/0000-0001-7769-7377)
- Peiqi Ma
- Yuqing Xin
- Yalei Wang (ORCID: https://orcid.org/0000-0002-7678-349X)
Institutions
- Fuyang City People's Hospital (CN)
- Fuyang Maternity and Child Health Care Hospital (CN)
- Fuyang Second People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-06-30
- DOI
- https://doi.org/10.3389/fonc.2025.1539537
- Citations
- 1
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.52