59 citations · 126 across the 11 of their papers we have counts for
12 papers
Automated Volumetric Segmentation of Microaneurysms on OCT Using Artificial Intelligence
Min Gao, Yukun Guo, Tristan T. Hormel +5
Purpose: To develop and validate a deep learning-based method for the automated identification and volumetric segmentation of microaneurysms (MAs) in diabetic retinopathy (DR) usin…
Deep Learning-assisted AMD Staging based on OCT and OCT Angiography
Yukun Guo, Tristan T. Hormel, An-Lun Wu +4
To develop and evaluate deep learning models for automated grading of age-related macular degeneration (AMD) severity using optical coherence tomography (OCT) and OCT angiography (…
Three-Dimensional Retinal Microvasculature Restoration in OCT Angiography
Yukun Guo, Min Gao, Tristan T. Hormel +3
Optical coherence tomographic angiography (OCTA) is a powerful technique for imaging retinal microvasculature. However, acquiring reliable quantification of retinal blood flow and…
Robust Detection of Retinal Neovascularization in Widefield Optical Coherence Tomography
Jinyi Hao, Jie Wang, Liqin Gao +8
Retinal neovascularization (RNV) is a vision threatening development in diabetic retinopathy (DR). Vision loss associated with RNV is preventable with timely intervention, making R…
AI-derived layer-specific OCT biomarkers for classification of geographic atrophy
Yukun Guo, An-Lun Wu, Tristan T. Hormel +5
Geographic atrophy (GA) is a key biomarker of dry age-related macular degeneration (AMD) traditionally identified through color fundus photography. Hyper-transmission defects (hype…
Nonperfused Retinal Capillaries -- A New Method Developed on OCT and OCTA
Min Gao, Yukun Guo, Tristan T. Hormel +6
To develop a new method to quantify nonperfused retinal capillaries (NPCs) by using co-registered optical coherence tomography (OCT) and OCT angiography (OCTA), and to evaluate NPC…
Perfused and Nonperfused Microaneurysms Identified and Characterized by Structural and Angiographic OCT
Min Gao, Tristan T. Hormel, Yukun Guo +5
Purpose: Microaneurysms (MAs) have distinct, oval-shaped, hyperreflective walls on structural OCT, and inconsistent flow signal in the lumen with OCT angiography (OCTA). Their rela…
Interpretable Diabetic Retinopathy Diagnosis based on Biomarker Activation Map
Pengxiao Zang, Tristan T. Hormel, Jie Wang +6
Deep learning classifiers provide the most accurate means of automatically diagnosing diabetic retinopathy (DR) based on optical coherence tomography (OCT) and its angiography (OCT…
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…