Jui-Kai Wang

Assistant Professor

University of Texas Southwestern Medical Center

United States

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Dr. Jui-Kai Wang is an Assistant Professor at The University of Texas Southwestern Medical Center, USA. His research focuses on applying deep learning techniques to ophthalmology, particularly in differentiating retinal conditions such as papilledema and non-arteritic anterior ischemic optic neuropathy. His recent publications explore advancements in optical coherence tomography and machine learning for retinal image analysis and classification.

Articles (10)

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2024

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2024

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2024

Collaborators (4)

Isabella Grumbach

Iowa State University

UNITED STATES

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Muhammad Imran

Florida State University

UNITED STATES

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Daniel Hyer

Associate Professor

Iowa State University

UNITED STATES

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Mona Garvin

Iowa State University

UNITED STATES

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Jui-Kai Wang

Research Interests

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About

Articles (10)

Deep Learning Differentiates Papilledema, NAION, and Healthy Eyes With Unsegmented 3D OCT Volumes

RetinaRegNet: A zero-shot approach for retinal image registration

Deep Learning Approach Readily Differentiates Papilledema, Non-Arteritic Anterior Ischemic Optic Neuropathy, and Healthy Eyes

Laser Speckle Flowgraphy Reveals Widespread Reductions in Ocular Blood Flow in nonexudative Age-Related Macular Degeneration

Radiation effects on retinal layers revealed by OCT, OCT-A, and perimetry as a function of dose and time from treatment.

Archetypal Analysis Reveals Consistent Visual Field Patterns for Stimulus Sizes III and V in Glaucoma and NAION

Classifying and quantifying changes in papilloedema using machine learning

Hybrid deep learning and optimal graph search method for optical coherence tomography layer segmentation in diseases affecting the optic nerve

Macular patterns of neuronal and visual field loss in recovered optic neuritis identified by machine learning

Quantifying the spatial patterns of retinal ganglion cell loss and progression in optic neuropathy by applying a deep learning variational autoencoder approach to optical coherence tomography

Collaborators (4)

Isabella Grumbach

Muhammad Imran

Daniel Hyer

Mona Garvin

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