Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound
Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Observational
SUMMARY
This study aims to develop an ultrasound image-based deep learning system to enable automatic segmentation, T-staging, and pathological grading prediction of bladder tumors. It seeks to enhance the objectivity, accuracy, and efficiency of bladder cancer diagnosis, reduce reliance on physician experience, and provide support for precision medicine and resource optimization.
Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Maximum Age: 85
Healthy Volunteers: f
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Locations
Other Locations
China
Department of Urology, Peking University First Hospital
RECRUITING
Beijing
Contact Information
Primary
Zheng Zhang
doczhz@aliyun.com
+86 139 0137 1490
Time Frame
Start Date: 2025-05-27
Estimated Completion Date: 2026-05-31
Participants
Target number of participants: 400
Related Therapeutic Areas
Sponsors
Leads: Peking University First Hospital