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Multicenter Validation Clinical Study of an AI-Based X-ray Image Quality Control System

Multicenter Validation Clinical Study of an AI-Based X-ray Image Quality Control System

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600117349
Enrollment
Unknown
Registered
2026-01-22
Start date
2026-01-30
Completion date
Unknown
Last updated
2026-01-27

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

Conditions

None listed

Interventions

Gold Standard:Manual annotation on X-ray images
Index test:Results output by the AI-based X-ray image quality control system

Sponsors

West China Hospital, Sichuan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
1 Years to 100 Years

Inclusion criteria

Inclusion criteria: 1 Outpatient and inpatient X-ray images taken at each center from January 2025 to November 2025; 2 The body parts include: chest (frontal), chest (lateral), knee (frontal), knee (lateral), abdomen (frontal), lumbar spine (frontal), lumbar spine (lateral), cervical spine (frontal), cervical spine (lateral); 3 X-ray images are in original DICOM format and include necessary physical parameters.

Exclusion criteria

Exclusion criteria: 1 Poor image quality, anatomical structures cannot be recognized; 2 Image damage, incorrect format, missing physical parameters; 3 Duplicate images.

Design outcomes

Primary

MeasureTime frame
Body part classification accuracy (accuracy, precision, recall, F1 score);Positioning Result Classification Accuracy (Accuracy, Precision, Recall, F1 Score);Segmentation Accuracy (Dice);—

Secondary

MeasureTime frame
Sensitivity;Specificity;Digital x-ray images;—

Countries

China

Contacts

Public ContactZhenlin Li

West China Hospital, Sichuan University

lzlcd01@126.com+86 189 8060 2130

Outcome results

None listed

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