Yukun Zhou
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    • Independent Evaluation of RETFound Foundation Model's Performance on Optic Nerve Analysis Using Fundus Photography
    • Revealing the Impact of Pre-training Data on Medical Foundation Models
    • Revealing the Impact of Pre-training Data on Medical Foundation Models
    • Retinal Microvascular Biomarker Assessment With Automated Algorithm and Semiautomated Software in the Montrachet Dataset
    • How Generalizable Are Foundation Models When Applied to Different Demographic Groups and Settings?
    • A New Foundation Model for Multimodal Ophthalmic Images: Advancing Disease Detection and Prediction
    • Evaluating the Impact of Retinal Vessel Segmentation Metrics on Retest Reliability in a Clinical Setting: A Comparative Analysis Using AutoMorph
    • VCAN in the extracellular matrix drives glioma recurrence by enhancing cell proliferation and migration
    • A New Retest-Stable Tortuosity Metric for Retinal Vessel Analyses
    • Foundation models in ophthalmology
    • A Retest -Stable Vessel Tortuosiry Metric for Fundus Photography
    • Accelerate the pace toward open - source research for ophthalmology
    • Explore Vision-Language Model with Hierarchical Information for Multiple Retinal Disease Recognition
    • Oculomics in Bipolar Affective Disorder: Insights from Retinal Imaging
    • Predicting aortic stenosis from colour fundus photographs from the AlzEye Study using a deep learning model
    • Retinal morphological differences in atypical Parkinsonism: A cross-sectional analysis of the AlzEye cohort
    • Retinal morphological differences in atypical Parkinsonism: A crosssectional analysis of the AlzEye cohort
    • Retino-Vascular changes throughout the Menstrual Cycle: Associations with retinal imaging in UK Biobank
    • Unveiling Patterns of Retinal Imaging: Association of Menopause with Choroidal Thickness and Retinovascular Indices in UK Biobank
    • Cross-modality Labeling Enables Noninvasive Capillary Quantification as a Sensitive Biomarker for Assessing Cardiovascular Risk
    • Expectation maximisation pseudo labels
    • REMOTE DIGITAL SURVEILLANCE AND MACHINE LEARNING MODELLING TO PREDICT SURVIVAL FOLLOWING RADICAL CYSTECTOMY FOR BLADDER CANCER—A SECONDARY OUTCOME ANALYSIS OF THE IROC TRIAL
    • CF-Loss: Clinically-relevant feature optimised loss function for retinal multi-class vessel segmentation and vascular feature measurement
    • Generalisable Retinal Image Analysis for Disease Detection
    • Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease
    • A foundation model for generalizable disease detection from retinal images
    • Comment on \"Race distribution in non-arteritic anterior ischemic optic neuropathy\"
    • Age Prediction from Retinal Fundus Images and Segmented Vessel Images using Deep Learning
    • Associations of Retinal Vascular Morphology and Inflammatory Bowel Disease: A cross-sectional analysis.
    • Deep-learning fusion of OCT imaging and traditional risk factors to improve dementia detection in AlzEye
    • Optical coherence tomography for the prediction of major adverse cardiovascular events in AlzEye
    • Predicting major adverse cardiovascular events with colour fundus photograph in the AlzEye Study
    • Retinal biomarkers for systemic diseases: an oculome-wide association study in 164,784 individuals
    • MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations with Limited Labels
    • Association Between Retinal Features From Multimodal Imaging and Schizophrenia.
    • Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised Segmentation
    • Prognostic Imaging Biomarker Discovery in Survival Analysis for Idiopathic Pulmonary Fibrosis
    • Progressive Subsampling for Oversampled Data - Application to Quantitative MRI
    • AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline
    • Learning Morphological Feature Perturbations for Calibrated Semi-Supervised Segmentation
    • Generative Adversarial Networks for OCT Counterfactual Visual Explanations in Ophthalmic Imaging
    • Exploring Retinal Vascular Morphology via A Deep Learning Pipeline
    • Generalised Super Resolution for Quantitative MRI Using Self-supervised Mixture of Experts
    • Learning to Address Intra-segment Misclassification in Retinal Imaging
    • A refined equilibrium generative adversarial network for retinal vessel segmentation
    • Improving Knowledge Distillation via Category Structure
    • Geomagnetic Sensor Noise Reduction for Improving Calibration Compensation Accuracy Based on Improved HHT Algorithm
    • Dual-attention Focused Module for Weakly Supervised Object Localization
    • Spinning projectile's angular measurement using crest and trough data of a geomagnetic sensor
    • Calibration and compensation method of three-axis geomagnetic sensor based on pre-processing total least square iteration
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Generative Adversarial Networks for OCT Counterfactual Visual Explanations in Ophthalmic Imaging

Jun 1, 2022·
P Woodward-Court
,
PA Keane
,
D Alexander
,
Y Zhou
· 0 min read
Cite URL
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Manuscript
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ASSOC RESEARCH VISION OPHTHALMOLOGY INC
Last updated on Jun 1, 2022
← Learning Morphological Feature Perturbations for Calibrated Semi-Supervised Segmentation Jul 1, 2022
Exploring Retinal Vascular Morphology via A Deep Learning Pipeline May 1, 2022 →

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