5 citations · 10 across the 4 of their papers we have counts for
4 papers
Glorbit: A Modular, Web-Based Platform for AI Based Periorbital Measurement in Low-Resource Settings
George R. Nahass, Jacob van der Ende, Sasha Hubschman +9
Periorbital measurements such as margin reflex distances (MRD1/2), palpebral fissure height, and scleral show are essential in diagnosing and managing conditions like ptosis and ey…
Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images
George R. Nahass, Zhu Wang, Homa Rashidisabet +8
Machine unlearning aims to remove the influence of specific training samples from a trained model without full retraining. While prior work has largely focused on privacy-motivated…
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…