59 citations · 126 across the 9 of their papers we have counts for
4 papers · 1 filter
Automated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning
Yukun Guo, Tristan T. Hormel, Honglian Xiong +3
Purpose: We proposed a deep convolutional neural network (CNN), named Retinal Fluid Segmentation Network (ReF-Net) to segment volumetric retinal fluid on optical coherence tomograp…
DcardNet: Diabetic Retinopathy Classification at Multiple Levels Based on Structural and Angiographic Optical Coherence Tomography
Pengxiao Zang, Liqin Gao, Tristan T. Hormel +4
Objective: Optical coherence tomography (OCT) and its angiography (OCTA) have several advantages for the early detection and diagnosis of diabetic retinopathy (DR). However, automa…
High-resolution wide-field OCT angiography with a self-navigation method to correct microsaccades and blinks
Xiang Wei, Tristan T. Hormel, Yukun Guo +2
In this study, we demonstrate a novel self-navigated motion correction method that suppresses eye motion and blinking artifacts on wide-field optical coherence tomographic angiogra…
Reconstruction of high-resolution 6x6-mm OCT angiograms using deep learning
Min Gao, Yukun Guo, Tristan T. Hormel +3
Typical optical coherence tomographic angiography (OCTA) acquisition areas on commercial devices are 3x3- or 6x6-mm. Compared to 3x3-mm angiograms with proper sampling density, 6x6…