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LEAF(Liver Tumor dEtection And classiFication AI)
Sponsor: Zhejiang University
Summary
This study plans to utilize multiphase contrast-enhanced and non-contrast CT（Computed Tomography） images from 10000 pathologically confirmed liver tumor patients at our hospital. An AI（artificial intelligence） model will be used to outline the 3D contours of liver masses, which will then be refined by radiologists and hepatobiliary-pancreatic surgeons to enhance model accuracy. By incorporating more imaging data, the model's recognition capabilities will be improved, laying the groundwork for prospective clinical trials and aiming to establish a superior AI model for early liver cancer screening based on CT imaging.
Official title: Clinical Research on the Use of Abdominal CT Combined With AI for Early Screening
Key Details
Gender
All
Age Range
18 Years - 80 Years
Study Type
INTERVENTIONAL
Enrollment
10000
Start Date
2025-07-15
Completion Date
2030-09-15
Last Updated
2026-03-10
Healthy Volunteers
Yes
Conditions
Interventions
LEAF(Liver tumor dEtection And classiFication AI)
Using the LEAF(Liver tumor dEtection And classiFication AI)model to assist in image interpretation, patients with positive results are recalled for further examination based on the LEAF output information and the original image interpretation, to obtain pathological results and long-term follow-up.
Locations (1)
the First Affiliated Hospital, School of Medicine, Zhejiang University
Hangzhou, Zhejiang, China