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ARVO Annual Meeting Abstract June 2025

Axial length and layer thickness in the Rotterdam Study using the EyeNED layer segmentation algorithm

Karin van Garderen; Victor de Vries; Daniel Luttikhuizen; José Vargas Quiros; Jeroen Vermeulen; Bart Liefers; Caroline C W Klaver

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):571.

ARVO Annual Meeting Abstract June 2025

VascX: a deep learning pipeline for retinal vascular analysis from color fundus images

Jose David Vargas Quiros; Bart Liefers; Victor de Vries; Jeroen Vermeulen; Karin van Garderen; Caroline C W Klaver

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):561.

ARVO Annual Meeting Abstract June 2025

Deep learning analysis of retinal vasculature from color fundus photography reveals diagnostic and predictive value for open-angle glaucoma

Victor de Vries; José Vargas Quiros; Joëlle E. Vergroesen; Karin van Garderen; Bart Liefers; Caroline C W Klaver; Wishal D Ramdas

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):419.

ARVO Annual Meeting Abstract June 2025

Deep learning-based quantification of intermediate age-related macular degeneration biomarkers for predicting geographic atrophy and exudative AMD

Haras Mhmud; Eric F. Thee; Jeroen Vermeulen; Bart Liefers; Caroline C W Klaver

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):862.

Artificial Intelligence December 2024

CNN-Based Device-Agnostic Feature Extraction From ONH OCT Scans

PDF

Sjoerd J. Driessen; Karin A. van Garderen; Danilo Andrade De Jesus; Luisa Sanchez Brea; João Barbosa-Breda; Bart Liefers; Hans G. Lemij; Doreen Nelson-Ayifah; Angelina Ampong; Pieter W. M. Bonnemaijer; Alberta A. H. J. Thiadens; Caroline C. W. Klaver
TAGS: optic disk, biological markers, eye, retinal nerve fiber layer
Trans. Vis. Sci. Tech.. 2024; 13(12):5. https://doi.org/10.1167/tvst.13.12.5

Includes: Supplemental Content

ARVO Annual Meeting Abstract June 2024

Deep learning models for retinal vascular analysis from color fundus images

Jose David Vargas Quiros; Irene van Zeijl; Bart Liefers; Jeroen Vermeulen; Daniel Luttikhuizen; Amal Hamimida; Annemiek Krijnen; Karin Alida van Garderen; Corina Brussee; Magda A. Meester; Caroline C W Klaver

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):6188.

ARVO Annual Meeting Abstract June 2024

A vendor-independent platform for AI-assisted retinal image analysis

Bart Liefers; Jos Beekmans; Corina Brussee; Karin Alida van Garderen; Amal Hamimida; Annemiek Krijnen; Daniel Luttikhuizen; Magda A. Meester; Jose David Vargas Quiros; Jeroen Vermeulen; Irene van Zeijl; Caroline C W Klaver

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):5891.

ARVO Annual Meeting Abstract June 2024

The SD-OCT correlates of fundus autofluorescence in geographic atrophy: a comprehensive point-to-point analysis of fundus autofluorescence with SD-OCT using phase 3 trials DERBY and OAKS.

Konstantinos Balaskas; Bart Liefers; Robbert Struyven; siegfried wagner; Sophie Glinton; Gongyu Zhang; Livia Faes; Veronika Lipkova; Gunjan Naik; Pallavi Bagga; Praveen J Patel; Alex McKeown; Lukas Scheibler; Christine A Curcio; Dun Jack Fu

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):449.

ARVO Annual Meeting Abstract June 2024

AI-based qOCT analysis of phase 3 trials OAKS & DERBY data on the effect of pegcetacoplan on geographic atrophy

Pallavi Bagga; Dun Jack Fu; Bart Liefers; Robbert Struyven; Siegfried Wagner; Sophie Glinton; Gongyu Zhang; Livia Faes; Veronika Lipkova; Gunjan Naik; Praveen J Patel; Alex McKeown; Lukas Scheibler; Nikolas Pontikos; Ismail Moghul; Konstantinos Balaskas

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):3262.

ARVO Annual Meeting Abstract June 2024

Deep learning-based quantification of intermediate age-related macular degeneration features for the prediction of geographic atrophy and exudative AMD

Eric F. Thee; Haras Mhmud; Daniel Luttikhuizen; Bart Liefers; Caroline C W Klaver

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):4926.

ARVO Annual Meeting Abstract June 2023

Automated Deep Learning-based Disease Feature Quantification on Color Fundus Photographs for Prediction of Late-stage Age-related Macular Degeneration

Haras Mhmud; Eric F. Thee; Bart Liefers; Corina Brussee; Amal Hamimida; Irene van Zeijl; Annemiek Krijnen; Daniel Luttikhuizen; Caroline C W Klaver

Invest. Ophthalmol. Vis. Sci.. 2023; 64(8):218.

ARVO Annual Meeting Abstract June 2022

Automated drusen quantification for the prediction of late age-related macular degeneration

Eric F. Thee; Bart Liefers; Daniel T. Luttikhuizen; Caroline C W Klaver

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):3012 – F0282.

ARVO Annual Meeting Abstract June 2022

Deep learning-based detection of Plus disease of Retinopathy of Prematurity

Robbert R. R. Struyven; Siegfried Wagner; Bart Liefers; Gongyu Zhang; Sophie Glinton; Madeline Kelly; Meera Radia; Jonathan Than; Shafi Balal; Charles Hennings; Pakinee Pooprasert; Nikolas Pontikos; Pearse Andrew Keane; Praveen Patel; Gillian Adams; Konstantinos Balaskas

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):212 – F0059.

ARVO Annual Meeting Abstract June 2022

Development and external validation of a novel automatic segmentation model for detection and quantification of geographic atrophy from optical coherence tomography imaging

Dun Jack Fu; Tiarnan D L Keenan; Sophie Glinton; Livia Faes; Siegfried Wagner; Alex McKeown; Gongyu Zhang; Bart Liefers; Praveen Patel; Pearse Andrew Keane; Konstantinos Balaskas

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):2054 – F0043.

ARVO Annual Meeting Abstract June 2022

Eye2Gene: prediction of causal inherited retinal disease gene from multimodal imaging using AI

NIKOLAS PONTIKOS; William Woof; Peter Krawitz; Gavin Arno; Kristina Hess; Malena Daich Varela; Bart Liefers; Thales Guimaraes; Mital Shah; Savita Madhusudhan; Susan M. Downes; Konstantinos Balaskas; Omar Abdul Rahman Mahroo; Frank G Holz; Michel Michaelides; Andrew R Webster

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):1161.

ARVO Annual Meeting Abstract June 2021

Hierarchical curriculum learning for robust automated detection of low-prevalence retinal disease features: application to reticular pseudodrusen

Cristina González-Gonzalo; Eric F. Thee; Bart Liefers; Coen de Vente; Caroline C. W. Klaver; Clara I. Sánchez

Invest. Ophthalmol. Vis. Sci.. 2021; 62(8):86.

Articles March 2021

Reliability of Retinal Pathology Quantification in Age-Related Macular Degeneration: Implications for Clinical Trials and Machine Learning Applications

PDF

Philipp L. Müller; Bart Liefers; Tim Treis; Filipa Gomes Rodrigues; Abraham Olvera-Barrios; Bobby Paul; Narendra Dhingra; Andrew Lotery; Clare Bailey; Paul Taylor; Clarisa I. Sánchez; Adnan Tufail
TAGS: age-related macular degeneration, machine learning, pathology, reliability, drusen, diagnostic imaging
Trans. Vis. Sci. Tech.. 2021; 10(3):4. https://doi.org/10.1167/tvst.10.3.4

Includes: Supplemental Content

ARVO Annual Meeting Abstract July 2019

Familial discordance in disease phenotype in siblings with Stargardt disease

Dyon Valkenburg; Esmee Runhart; Bart Liefers; stanley lambertus; Clara I Sanchez; Frans P Cremers; nathalie m bax; Carel C B Hoyng

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):5015.

ARVO Annual Meeting Abstract July 2019

Opening the “black box” of deep learning in automated screening of eye diseases

Cristina González-Gonzalo; Bart Liefers; Akshayaa Vaidyanathan; Harm van Zeeland; Caroline C W Klaver; Clara I Sanchez

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):1443.

ARVO Annual Meeting Abstract July 2019

Prediction of areas at risk of developing geographic atrophy in color fundus images using deep learning

Bart Liefers; Johanna Maria Colijn; Cristina González-Gonzalo; Akshayaa Vaidyanathan; Harm van Zeeland; Paul Mitchell; Caroline C W Klaver; Clara I Sanchez

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):1455.

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Axial length and layer thickness in the Rotterdam Study using the EyeNED layer segmentation algorithm

VascX: a deep learning pipeline for retinal vascular analysis from color fundus images

Deep learning analysis of retinal vasculature from color fundus photography reveals diagnostic and predictive value for open-angle glaucoma

Deep learning-based quantification of intermediate age-related macular degeneration biomarkers for predicting geographic atrophy and exudative AMD

CNN-Based Device-Agnostic Feature Extraction From ONH OCT Scans

Deep learning models for retinal vascular analysis from color fundus images

A vendor-independent platform for AI-assisted retinal image analysis

The SD-OCT correlates of fundus autofluorescence in geographic atrophy: a comprehensive point-to-point analysis of fundus autofluorescence with SD-OCT using phase 3 trials DERBY and OAKS.

AI-based qOCT analysis of phase 3 trials OAKS & DERBY data on the effect of pegcetacoplan on geographic atrophy

Deep learning-based quantification of intermediate age-related macular degeneration features for the prediction of geographic atrophy and exudative AMD

Automated Deep Learning-based Disease Feature Quantification on Color Fundus Photographs for Prediction of Late-stage Age-related Macular Degeneration

Automated drusen quantification for the prediction of late age-related macular degeneration

Deep learning-based detection of Plus disease of Retinopathy of Prematurity

Development and external validation of a novel automatic segmentation model for detection and quantification of geographic atrophy from optical coherence tomography imaging

Eye2Gene: prediction of causal inherited retinal disease gene from multimodal imaging using AI

Hierarchical curriculum learning for robust automated detection of low-prevalence retinal disease features: application to reticular pseudodrusen

Reliability of Retinal Pathology Quantification in Age-Related Macular Degeneration: Implications for Clinical Trials and Machine Learning Applications

Familial discordance in disease phenotype in siblings with Stargardt disease

Opening the “black box” of deep learning in automated screening of eye diseases

Prediction of areas at risk of developing geographic atrophy in color fundus images using deep learning

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