Area of research
Ophthalmology · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include Glaucoma and retinal disorders, Retinal Imaging and Analysis, Retinal Diseases and Treatments, and Ophthalmology and Visual Impairment Studies.
Relationship of 24-2C Central Visual Field Damage to Juxtapapillary Choriocapillaris Dropout in Glaucoma Eyes With or Without Axial Myopia
Deep Learning Identifies High-Quality Fundus Photographs and Increases Accuracy in Automated Primary Open Angle Glaucoma Detection
Proactive Decision Support for Glaucoma Treatment: Predicting Surgical Interventions with Clinically Available Data
Evaluating glaucoma in myopic eyes: Challenges and opportunities
Diagnostic Accuracy of Optic Nerve Head and Macula OCT Parameters for Detecting Glaucoma in Eyes With and Without High Axial Myopia
Rates of Choriocapillaris Microvascular Dropout and Macular Structural Changes in Glaucomatous Optic Neuropathy With and Without Myopia
Wide-Field Optical Coherence Tomography Imaging Improves Rate of Change Detection in Progressing Glaucomatous Eyes Compared With Standard-Field Imaging
Central visual field damage in glaucoma eyes with choroidal microvasculature dropout with and without high axial myopia
Multimodal Deep Learning Classifier for Primary Open Angle Glaucoma Diagnosis Using Wide-Field Optic Nerve Head Cube Scans in Eyes With and Without High Myopia
Detecting Glaucoma from Fundus Photographs Using Deep Learning without Convolutions
Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning
Macula structural and vascular differences in glaucoma eyes with and without high axial myopia
Diagnostic Accuracy of Macular Thickness Map and Texture En Face Images for Detecting Glaucoma in Eyes With Axial High Myopia
Comparison of Optic Disc Ovality Index and Rotation Angle Measurements in Myopic Eyes Using Photography and OCT Based Techniques
Deep Learning Image Analysis of Optical Coherence Tomography Angiography Measured Vessel Density Improves Classification of Healthy and Glaucoma Eyes
The influence of axial myopia on optic disc characteristics of glaucoma eyes
Deep Learning Estimation of 10-2 and 24-2 Visual Field Metrics Based on Thickness Maps from Macula OCT
Individualized Glaucoma Change Detection Using Deep Learning Auto Encoder-Based Regions of Interest
Bruch Membrane Opening Detection Accuracy in Healthy Eyes and Eyes With Glaucoma With and Without Axial High Myopia in an American and Korean Cohort
Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms
Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps
Relationship of Corneal Hysteresis and Anterior Lamina Cribrosa Displacement in Glaucoma
Racial Differences in the Association of Anterior Lamina Cribrosa Surface Depth and Glaucoma Severity in the African Descent and Glaucoma Evaluation Study (ADAGES)
Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs
Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression
Racial Differences in Rate of Change of Spectral-Domain Optical Coherence Tomography–Measured Minimum Rim Width and Retinal Nerve Fiber Layer Thickness
Automated Beta Zone Parapapillary Area Measurement to Differentiate Between Healthy and Glaucoma Eyes
Reproducibility of Optical Coherence Tomography Angiography Macular and Optic Nerve Head Vascular Density in Glaucoma and Healthy Eyes
Comparing the Rates of Retinal Nerve Fiber Layer and Ganglion Cell–Inner Plexiform Layer Loss in Healthy Eyes and in Glaucoma Eyes
A Longitudinal Analysis of Peripapillary Choroidal Thinning in Healthy and Glaucoma Subjects