Biparametric magnetic resonance imaging-based radiomics model can improve the detection of dense and sparse prostate cancers
The radiomics model based on bpMRI can effectively improve the detection of PCa lesions, especially sparse lesions, and significantly reduce missed diagnoses.
Authors
- Liangping Zhou (ORCID: https://orcid.org/0000-0001-7051-5868)
- Xiaohang Liu
- Bingni Zhou
- Rong Li (ORCID: https://orcid.org/0000-0003-2880-1195)
- Hong Lv
- Hualei Gan
- Zhangzhe Chen
- Yajia Gu
- Ting Wang (ORCID: https://orcid.org/0000-0003-1486-9156)
Institutions
- Shanghai Medical College of Fudan University (CN)
- Sun Yat-sen University (CN)
- Fudan University (CN)
- Fudan University Shanghai Cancer Center (CN)
- Zhongshan Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- YangPu Geriatric Hospital (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-09-24
- DOI
- https://doi.org/10.21037/qims-2024-2912
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00