Leveraging Deep Learning in Real-Time Intelligent Bladder Tumor Detection During Cystoscopy: A Diagnostic Study
HRNetV2 demonstrated excellent performance, particularly with high-resolution images, offering high sensitivity and precision in bladder lesion detection. The results suggest that HRNetV2 has significant potential to improve detection accuracy in clinical practice. Future work should focus on optimizing the model further and testing it with larger, multicenter datasets.
Authors
- Zhigang Ji (ORCID: https://orcid.org/0000-0003-3834-6579)
- Zixing Ye
- Yujiao Sun
- Chengqing He
- Yingjie Li (ORCID: https://orcid.org/0000-0001-6091-8911)
- Guanglin He
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- Hikvision (China)
Publication Details
- Journal
- Annals of Surgical Oncology
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1245/s10434-025-17015-3
- Citations
- 7
- Primary Topic
- Bladder and Urothelial Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 14.04
Funders
- China Primary Health Care Foundation