Deep Learning Optical Coherence Tomography (OCT) and OCT Angiography (OCTA) in NVC

Deep Learning OCT and OCTA Quantification in Neovascular Age Related Macular Degeneration

To evaluate the activity of neovascular macula degeneretion as assessed by SD-OCTand OCT-A using a split-person study design and deep-learning quantification.

Exudative neovascular macular degeneration is the primarily an age-related retinal condition The optical coherence tomography angiography represents a novel and noninvasive diagnostic technique that allows a detailed and quantitative analysis of retinal and choriocapillary vascular features in order to choose the best therapy .

The study evaluates the changes in structural optical coherence tomography and optical coherence tomography angiography features in neovascular macular degeration patients undergoing ANTI-VEGF treatments using artificial intelligence.

Inclusion Criteria: age older than 50 years

• diagnosis of neovascular macular degeneration
• absence of previous retinal surgery and congenital eye diseases.
• absence of errors of refraction
• absence of lens opacities
• absence of low-quality OCT and OCTA images

Exclusion Criteria:• age younger than 50 years

• previous retinal surgery and congenital eye diseases
• errors of refraction
• lens opacities
• low-quality OCT and OCTA images