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Research on the Application Value of Deep Learning Reconstruction Technology in Liver Imaging

Research on the Application Value of Deep Learning Reconstruction Technology in Liver Imaging

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500104408
Enrollment
Unknown
Registered
2025-06-17
Start date
2025-03-23
Completion date
Unknown
Last updated
2025-06-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Multiple Hepatic Disorders

Interventions

Observation Group :None

Sponsors

Sun Yat-sen Memorial Hospital, Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: First, the liver was examined by prmesteride contrast enhancement, and second, there was a lesion (benign and malignant).

Exclusion criteria

Exclusion criteria: Liver examination with Fepromexan

Design outcomes

Primary

MeasureTime frame
Signal-to-Noise Ratio (SNR) of the Hepatic Parenchyma;Contrast-to-Noise Ratio (CNR) between the Lesion and Hepatic Parenchyma;Contrast Ratio (CR) of the Lesion;—

Countries

China

Contacts

Public ContactLai Bingjia

Sun Yat-sen Memorial Hospital, Sun Yat-sen University

laibj3@mail.sysu.edu.cn+86 135 4432 0054

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026