Diabetic macular edema Diabetic retinopathy,
Conditions
Interventions
The OCT central subfield thickness at macular area which is manually measured together with retinal fundus are used to train the algorithm to detect diabetic macular edema.,The retinal fundus images a
Screening,Screening
Algorithm training group,Algorithm validation group
Sponsors
Rajavithi hospital
Eligibility
Sex/Gender
All
Age
18 Years to No maximum
Inclusion criteria
Inclusion criteria: Diabetic patient with retinal images(45 degree with macular-center) and OCT images which is macular dense volume scan (49 high-speed B-scans [512 A scan/B scan]; 20x20 degree, 6x6 mm were taken on the same date. Naiive patients with no previous treatment
Exclusion criteria
Exclusion criteria: Patient with retinal or macular disease which distort the interpretation of OCT images such as choroidal neovascularization, retinal vein occlusion, postsurgical macular edema, central serous chorioretinopathy, macular retinal detachment, epiretinal membrane, macular hole, or vitreomacular traction retinal images with poor quality
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| To develope the deep learning system from OCT imaging to detect diabetic macular edema from color fu 1 year Algorithm | — |
Secondary
| Measure | Time frame |
|---|---|
| Effectiveness of deep learning algorithm in screening for diabetic macular edema 1 year sensitivity,specificity, accuracy, area under the curve comparing with retinal specialists | — |
Countries
Thailand
Contacts
Public ContactPaisan Ruamviboonsuk
Rajavithi hospital
Outcome results
None listed