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Artificial Intelligence July 2024

Multi-Plexus Nonperfusion Area Segmentation in Widefield OCT Angiography Using a Deep Convolutional Neural Network

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Yukun Guo; Tristan T. Hormel; Min Gao; Qisheng You; Jie Wang; Christina J. Flaxel; Steven T. Bailey; Thomas S. Hwang; Yali Jia
TAGS: angiogram, convolutional neural networks, nasopharyngeal aspirate, artifacts, deep learning
Trans. Vis. Sci. Tech.. 2024; 13(7):15. https://doi.org/10.1167/tvst.13.7.15

ARVO Imaging in the Eye Conference Abstract July 2024

Geographic Atrophy Segmentation on Optical Coherence Tomography

Yukun Guo; Tristan T. Hormel; Min Gao; Steven T. Bailey; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2024; 65(9):PB0091.

ARVO Imaging in the Eye Conference Abstract July 2024

Panretinal high-resolution OCT angiography for rodent imaging

Guangru Ben Liang; Tristan T. Hormel; Shuibin Ni; Yifan Jian; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2024; 65(9):PP0013.

ARVO Annual Meeting Abstract June 2024

Attention-Based Biomarker Activation Map: an Interpretability Method Specifically Designed for Deep-Learning-Aided Eye Disease Diagnosis

Pengxiao Zang; Tristan T Hormel; Thomas S Hwang; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):1589.

ARVO Annual Meeting Abstract June 2024

OCT angiography with optimized numerical k-sampling

Naixing Huang; Tristan T Hormel; Guangru Ben Liang; Xiang Wei; Yukun Guo; Siyu Chen; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):5519.

ARVO Annual Meeting Abstract June 2024

Wide-Field Swept-source structural OCT and OCT Angiography in Inherited Retinal Dystrophies

Xiao Zhou; Nida Wongchaisuwat; Guangru Ben Liang; Tristan T Hormel; Lesley Everett; Paul Yang; Mark E Pennesi; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):5495.

ARVO Annual Meeting Abstract June 2024

Non-human primate retinal imaging using wide-field swept-source OCT angiography for insight into disease etiology

Tristan T Hormel; Xiang Wei; Lauren Renner; Martha Neuringer; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):3887.

ARVO Annual Meeting Abstract June 2024

En face Visualization and Quantification of Hyper-reflective Henle's Fiber Layer in Age-related Macular Degeneration with Optical Coherence Tomography

Jie Wang; Carol Wang; Tristan T Hormel; Steven T Bailey; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):3261.

ARVO Annual Meeting Abstract June 2024

Retinal nonperfused capillaries identified and characterized by OCT and OCTA

Min Gao; Yukun Guo; Tristan T Hormel; Jie Wang; Thomas S Hwang; Steven Bailey; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):4332.

ARVO Annual Meeting Abstract June 2024

Quantifying and visualizing more features in diabetic retinopathy using ultrawide-field optical coherence tomography and deep-learning algorithms

Yukun Guo; Min Gao; Tristan T Hormel; Thomas S Hwang; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):2412.

ARVO Imaging in the Eye Conference Abstract June 2023

Quantifying Choriocapillaris Flow Deficits in Diabetic Retinopathy using Projection-resolved Optical Coherence Tomographic Angiography

JIE WANG; Tristan T. Hormel; Steven Bailey; Thomas Hwang; David Huang; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2023; 64(9):PP0020.

ARVO Annual Meeting Abstract June 2023

High-resolution wide-field single-shot panretinal imaging enabled by swept-source OCT angiography

Tristan Hormel; Guangru Ben Liang; Xiang Wei; Yukun Guo; Min Gao; Jie Wang; Steve Bailey; Thomas S Hwang; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2023; 64(8):4422.

ARVO Annual Meeting Abstract June 2023

3D Quantitative Analysis of Retinal Ischemia based on Oxygen Diffusion Model using Optical Coherence Tomography Angiography

Pengxiao Zang; Tristan Hormel; Thomas S Hwang; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2023; 64(8):3834.

ARVO Annual Meeting Abstract June 2023

Background noise-resolved and enhanced OCT angiography using an end-to-end convolutional neural network

Min Gao; Yukun Guo; Tristan Hormel; Jie Wang; Thomas S Hwang; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2023; 64(8):2365.

Artificial Intelligence April 2023

Deep Learning for Diagnosing and Segmenting Choroidal Neovascularization in OCT Angiography in a Large Real-World Data Set

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Jie Wang; Tristan T. Hormel; Kotaro Tsuboi; Xiaogang Wang; Xiaoyan Ding; Xiaoyan Peng; David Huang; Steven T. Bailey; Yali Jia
TAGS: choroidal neovascularization, datasets, angiogram, tissue membrane, deep learning
Trans. Vis. Sci. Tech.. 2023; 12(4):15. https://doi.org/10.1167/tvst.12.4.15

Artificial Intelligence July 2022

A Diabetic Retinopathy Classification Framework Based on Deep-Learning Analysis of OCT Angiography

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Pengxiao Zang; Tristan T. Hormel; Xiaogang Wang; Kotaro Tsuboi; David Huang; Thomas S. Hwang; Yali Jia
TAGS: angiogram, deep learning, diabetic retinopathy, eye, fundus photography, maps, cell adhesion molecules
Trans. Vis. Sci. Tech.. 2022; 11(7):10. https://doi.org/10.1167/tvst.11.7.10

Includes: Supplemental Content

ARVO Annual Meeting Abstract June 2022

A Deep Learning-based Method for Retinal Layer and Drusen Segmentation on Optical Coherence Tomography

Yukun Guo; Tristan Hormel; Min Gao; Thomas S Hwang; Steven T Bailey; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):3001 – F0271.

ARVO Annual Meeting Abstract June 2022

Artificial Intelligence-assisted Projection-resolved Optical Coherence Tomographic Angiography (aiPR-OCTA)

JIE WANG; Tristan Hormel; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):2910 – F0063.

ARVO Annual Meeting Abstract June 2022

Identification and characterization of microaneurysm in OCT and OCT angiography

Min Gao; Tristan Hormel; Yukun Guo; Steven T. Bailey; Christina J Flaxel; David Huang; Thomas S Hwang; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):2899 – F0052.

ARVO Annual Meeting Abstract June 2022

Generative-adversarial-learning-based biomarker activation map for improving the interpretability of deep-learning-aided diabetic retinopathy screening

Pengxiao Zang; Tristan Hormel; Jie Wang; Steven T. Bailey; Christina J Flaxel; David Huang; Thomas S Hwang; Yali Jia

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):211 – F0058.

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Multi-Plexus Nonperfusion Area Segmentation in Widefield OCT Angiography Using a Deep Convolutional Neural Network

Geographic Atrophy Segmentation on Optical Coherence Tomography

Panretinal high-resolution OCT angiography for rodent imaging

Attention-Based Biomarker Activation Map: an Interpretability Method Specifically Designed for Deep-Learning-Aided Eye Disease Diagnosis

OCT angiography with optimized numerical k-sampling

Wide-Field Swept-source structural OCT and OCT Angiography in Inherited Retinal Dystrophies

Non-human primate retinal imaging using wide-field swept-source OCT angiography for insight into disease etiology

En face Visualization and Quantification of Hyper-reflective Henle's Fiber Layer in Age-related Macular Degeneration with Optical Coherence Tomography

Retinal nonperfused capillaries identified and characterized by OCT and OCTA

Quantifying and visualizing more features in diabetic retinopathy using ultrawide-field optical coherence tomography and deep-learning algorithms

Quantifying Choriocapillaris Flow Deficits in Diabetic Retinopathy using Projection-resolved Optical Coherence Tomographic Angiography

High-resolution wide-field single-shot panretinal imaging enabled by swept-source OCT angiography

3D Quantitative Analysis of Retinal Ischemia based on Oxygen Diffusion Model using Optical Coherence Tomography Angiography

Background noise-resolved and enhanced OCT angiography using an end-to-end convolutional neural network

Deep Learning for Diagnosing and Segmenting Choroidal Neovascularization in OCT Angiography in a Large Real-World Data Set

A Diabetic Retinopathy Classification Framework Based on Deep-Learning Analysis of OCT Angiography

A Deep Learning-based Method for Retinal Layer and Drusen Segmentation on Optical Coherence Tomography

Artificial Intelligence-assisted Projection-resolved Optical Coherence Tomographic Angiography (aiPR-OCTA)

Identification and characterization of microaneurysm in OCT and OCT angiography

Generative-adversarial-learning-based biomarker activation map for improving the interpretability of deep-learning-aided diabetic retinopathy screening

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