5 citations · 11 across the 7 of their papers we have counts for
3 papers · 1 filter
Trends, Challenges, and Future Directions in Deep Learning for Glaucoma: A Systematic Review
Mahtab Faraji, Homa Rashidisabet, George R. Nahass +3
Here, we examine the latest advances in glaucoma detection through Deep Learning (DL) algorithms using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).…
Open-Source Periorbital Segmentation Dataset for Ophthalmic Applications
George R. Nahass, Emma Koehler, Nicholas Tomaras +10
Periorbital segmentation and distance prediction using deep learning allows for the objective quantification of disease state, treatment monitoring, and remote medicine. However, t…
State-of-the-Art Periorbital Distance Prediction and Disease Classification Using Periorbital Features
George R. Nahass, Sasha Hubschman, Jeffrey C. Peterson +9
Periorbital distances are critical markers for diagnosing and monitoring a range of oculoplastic and craniofacial conditions. Manual measurement, however, is subjective and prone t…