activity
20202026
most citedAutomated segmentation of retinal fluid volumes from structural and angiographic optical coherence tomography using deep learning

59 citations · 123 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2026

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 (…

cs.CV2026

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…

eess.IV2025

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…

q-bio.QM2025

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…

q-bio.QM2024

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…

q-bio.QM2023★ 23 cited

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…

eess.IV2022★ 3 cited

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…

eess.IV2020★ 59 cited

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…

physics.med-ph2020★ 36 cited

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…

eess.IV2020★ 2 cited

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…