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Research of Automated Maculopathy Screening Based on AI Techniques Using OCT Images

Maculopathy Clinical Trial

Official title:
Research of Automated Maculopathy Screening by Optical Coherent Tomography Image-based Deep Learning Techniques

Clinical Trial 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.

Clinical Trial 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. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT03476291
Study type Observational
Source The First Affiliated Hospital with Nanjing Medical University
Contact
Status Active, not recruiting
Phase
Start date June 30, 2017
Completion date December 31, 2020
View Details
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