Trials / Unknown
UnknownNCT03476291
Research of Automated Maculopathy Screening Based on AI Techniques Using OCT Images
Research of Automated Maculopathy Screening by Optical Coherent Tomography Image-based Deep Learning Techniques
- Status
- Unknown
- Phase
- —
- Study type
- Observational
- Enrollment
- 20,000 (estimated)
- Sponsor
- The First Affiliated Hospital with Nanjing Medical University · Academic / Other
- Sex
- All
- Age
- —
- Healthy volunteers
- —
Summary
The investigators expect to develop an algorithm that can interpret OCT images and automated determine whether the macula is normal or not by using OCT image-based deep learning techniques. And investigators wish to develop software applications that will help better screen and diagnose macular diseases in resource-limited areas.
Detailed description
The investigators will apply deep learning convolutional neural network by using ImageNet for an automated detection of multiple retinal diseases with OCT horizontal B-scans with a high-quality labeled database. Datasets, including training dataset, testing dataset and validation datasets, will be built by ophthalmologists of the First affiliated hospital of Nanjing Medical University according to the standardized annotation guidelines.
Conditions
Timeline
- Start date
- 2017-06-30
- Primary completion
- 2018-06-01
- Completion
- 2020-12-31
- First posted
- 2018-03-26
- Last updated
- 2018-03-26
Locations
1 site across 1 country: China
Source: ClinicalTrials.gov record NCT03476291. Inclusion in this directory is not an endorsement.