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Artificial Intelligence System for Assessing Image Quality of Slit-Lamp Images and Its Effects on Diagnosis

NCT04314180 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 300

Last updated 2020-03-19

No results posted yet for this study

Summary

Slit-lamp images are widely used in ophthalmology for the detection of cataract, keratopathy and other anterior segment disorders. In real-world practice, the quality of slit-lamp images can be unacceptable, which can undermine diagnostic accuracy and efficiency. Here, the researchers established and validated an artificial intelligence system to achieve automatic quality assessment of slit-lamp images upon capture. This system can also provide guidance to photographers according to the reasons for low quality.

Conditions

  • Anterior Segment Disorders
  • Artificial Intelligence

Interventions

DEVICE

Taking slit-lamp images

The participant only needs to take several slit-lamp images as usual.

Sponsors & Collaborators

  • Sun Yat-sen University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-02-01
Primary Completion
2020-07-01
Completion
2020-07-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04314180 on ClinicalTrials.gov