4 papers
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…
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…
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…
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…