2 citations · 2 across the 2 of their papers we have counts for
5 papers
Assessing glaucoma in retinal fundus photographs using Deep Feature Consistent Variational Autoencoders
Sayan Mandal, Alessandro A. Jammal, Felipe A. Medeiros
One of the leading causes of blindness is glaucoma, which is challenging to detect since it remains asymptomatic until the symptoms are severe. Thus, diagnosis is usually possible…
Bayesian Non-Parametric Factor Analysis for Longitudinal Spatial Surfaces
Samuel I. Berchuck, Mark Janko, Felipe A. Medeiros +2
We introduce a Bayesian non-parametric spatial factor analysis model with spatial dependency induced through a prior on factor loadings. For each column of the loadings matrix, spa…
Scalable Modeling of Spatiotemporal Data using the Variational Autoencoder: an Application in Glaucoma
Samuel I. Berchuck, Felipe A. Medeiros, Sayan Mukherjee
As big spatial data becomes increasingly prevalent, classical spatiotemporal (ST) methods often do not scale well. While methods have been developed to account for high-dimensional…
Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photos
Sonia Phene, R. Carter Dunn, Naama Hammel +17
Glaucoma is the leading cause of preventable, irreversible blindness world-wide. The disease can remain asymptomatic until severe, and an estimated 50%-90% of people with glaucoma…
From Machine to Machine: An OCT-trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs
Felipe A. Medeiros, Alessandro A. Jammal, Atalie C. Thompson
Previous approaches using deep learning algorithms to classify glaucomatous damage on fundus photographs have been limited by the requirement for human labeling of a reference trai…