Trials / Unknown
UnknownNCT04289064
Artificial Intelligence System for Assessing Image Quality of Fundus Images and Its Effects on Diagnosis
Artificial Intelligence System for Assessing Image Quality of Fundus Images and Its Effects on Diagnosis: A Clinical Trial
- Status
- Unknown
- Phase
- —
- Study type
- Observational
- Enrollment
- 300 (estimated)
- Sponsor
- Sun Yat-sen University · Academic / Other
- Sex
- All
- Age
- —
- Healthy volunteers
- Accepted
Summary
Fundus images are widely used in ophthalmology for the detection of diabetic retinopathy, glaucoma and other diseases. In real-world practice, the quality of fundus 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 fundus images upon capture. This system can also provide guidance to photographers according to the reasons for low quality.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| DEVICE | Taking a fundus image | The participant only needs to take a fundus image as usual. |
Timeline
- Start date
- 2020-02-01
- Primary completion
- 2020-07-01
- Completion
- 2020-07-01
- First posted
- 2020-02-28
- Last updated
- 2020-02-28
Locations
1 site across 1 country: China
Source: ClinicalTrials.gov record NCT04289064. Inclusion in this directory is not an endorsement.