Artificial Intelligence System for Assessing Image Quality of Fundus Images and Its Effects on Diagnosis
- Conditions
- Artificial IntelligenceRetinal Diseases
- Registration Number
- NCT04289064
- Lead Sponsor
- Sun Yat-sen University
- Brief 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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 300
- Patients should be aware of the contents and signed for the informed consent.
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- Patients who cannot cooperate with a photographer such as some paralytics, the patients with dementia and severe psychopaths.
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- Patients who do not agree to sign informed consent.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Performance of artificial intelligence system for distinguish between good image quality and poor image quality 3 months Area under the receiver operating characteristic curves, sensitivity, specificity, positive and negative predictive values, accuracy
- Secondary Outcome Measures
Name Time Method The comparison of the performance for previous artificial intelligence diagnostic system with fundus images of different image quality 3 months Cohen's kappa coefficient, P value and other related statistic results
Related Research Topics
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Trial Locations
- Locations (1)
Zhongshan Ophthalmic Center, Sun Yat-sen University
🇨🇳Guangzhou, Guangdong, China
Zhongshan Ophthalmic Center, Sun Yat-sen University🇨🇳Guangzhou, Guangdong, China