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ARVO Annual Meeting Abstract June 2025

Deep Learning-based Image Quality Assessment for Optical Coherence Tomography

Hemanth Machavaram; Derrek Hibar; Mike Chen; Alessandra Valcarcel; Vivide Chang; Thomas Albrecht; Daniela Ferrara; Huanxiang Lu

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):5418.

ARVO Annual Meeting Abstract June 2025

Structure-function correlations in GA using AI-based retinal layers lossmeasurements on OCT

Catherine A Cukras; Kenta Yoshida; Miao Zhang; Adam Pely; Verena Steffen; Simon S. Gao; Usha Chakravarthy; Christina Rabe; Sascha Fauser; Daniela Ferrara

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):4588.

ARVO Annual Meeting Abstract June 2025

The challenging assessment of foveal involvement in geographic atrophy (GA) on spectral-domain optical coherence tomography (SD-OCT)

Michael H. Chen; Phuong Phan; Dinah Chen; Katie M Litts; Verena Steffen; Siva Balasubramanian; Simon S. Gao; Usha Chakravarthy; Robyn H Guymer; Daniela Ferrara; Neha Anegondi

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):3488.

ARVO Annual Meeting Abstract June 2025

The impact of multimodal retinal imaging registration for deep-learning segmentation algorithms in geographic atrophy

Julia Cluceru; Aidan Bayer-Calvert; Neha Anegondi; Simon S. Gao; Daniela Ferrara; Christina Rabe

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):4176.

ARVO Annual Meeting Abstract June 2025

Repeatability Study for Retinal Optical Coherence Tomography (OCT) Segmentation Algorithms (ROSA) in neovascular age-related macular degeneration (nAMD)

Thomas Albrecht; Derrek Hibar; Mike Chen; Vivide Chang; Daniela Ferrara; Huanxiang Lu

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):578.

ARVO Annual Meeting Abstract June 2025

Future optical coherence tomography image generation for anatomical treatment response prediction

Yusuke Kikuchi; Xue Li; Neha Anegondi; Acner Camino Benech; Michael H. Chen; Katie M Litts; Andreas Maunz; Matthew Kornelius McLeod; Daniela Ferrara; Qi Yang

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):5477.

ARVO Annual Meeting Abstract June 2025

Deep learning (DL) to predict faricimab treatment response in diabetic macular edema (DME) using color fundus photos and clinical data

Matthew Kornelius McLeod; Javid Abderezaei; Acner Camino Benech; Yusuke Kikuchi; Chen Chen; Daniela Ferrara; Qi Yang; Neha Anegondi

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):5450.

ARVO Annual Meeting Abstract June 2025

Oral Antioxidant and Lutein Supplements are not Associated with Geographic Atrophy Progression in Age-related Macular Degeneration

Neha Anegondi; Verena Steffen; Daniela Ferrara; Christopher Brittain; Catherine A Cukras

Invest. Ophthalmol. Vis. Sci.. 2025; 66(8):3678.

Artificial Intelligence February 2025

Deep Learning Approaches to Predict Geographic Atrophy Progression Using Three-Dimensional OCT Imaging

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Kenta Yoshida; Neha Anegondi; Adam Pely; Miao Zhang; Frederic Debraine; Karthik Ramesh; Verena Steffen; Simon S. Gao; Catherine Cukras; Christina Rabe; Daniela Ferrara; Richard F. Spaide; SriniVas R. Sadda; Frank G. Holz; Qi Yang
TAGS: age-related macular degeneration, nonexudative, datasets, deep learning, diagnostic imaging, growth rate
Trans. Vis. Sci. Tech.. 2025; 14(2):11. https://doi.org/10.1167/tvst.14.2.11

Includes: Supplemental Content

Retina December 2024

Clinical and Imaging Characteristics of PRPH2 Retinopathies in a Longitudinal Cohort and Diagnostic Implications

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Johanna M. Seddon; Dikha De; Laura Grunenkovaite; Daniela Ferrara
TAGS: cohort studies, diagnostic imaging, genetic pedigree, genetics, phenotype, retinal diseases, visual acuity, atrophoderma maculatum, genes, heterozygote
Invest. Ophthalmol. Vis. Sci.. 2024; 65(14):31. https://doi.org/10.1167/iovs.65.14.31

Artificial Intelligence August 2024

Topographic Clinical Insights From Deep Learning–Based Geographic Atrophy Progression Prediction

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Julia Cluceru; Neha Anegondi; Simon S. Gao; Aaron Y. Lee; Eleonora M. Lad; Usha Chakravarthy; Qi Yang; Verena Steffen; Michel Friesenhahn; Christina Rabe; Daniela Ferrara
TAGS: ablation, age-related macular degeneration, nonexudative, datasets, deep learning, masks, diagnostic imaging, growth rate, pixel, shape
Trans. Vis. Sci. Tech.. 2024; 13(8):6. https://doi.org/10.1167/tvst.13.8.6

Includes: Supplemental Content

ARVO Annual Meeting Abstract June 2024

Generalizability of foundation models for geographic atrophy (GA) lesion segmentation in fundus autofluorescence (FAF)

Eric Gros; Matthew McLeod; Yusuke Kikuchi; Julia Cluceru; Neha Anegondi; Simon S. Gao; Christina Rabe; Daniela Ferrara; Qi Yang

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):2391.

ARVO Annual Meeting Abstract June 2024

Predicting functional outcomes for different treatment durations of faricimab in diabetic macular edema (DME)

Yusuke Kikuchi; Javid Abderezaei; Matthew McLeod; Chen Chen; Acner Camino Benech; Daniela Ferrara; Neha Anegondi; Qi Yang

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):3754.

ARVO Annual Meeting Abstract June 2024

Faricimab treatment response prediction in diabetic macular edema (DME) using deep learning on optical coherence tomography (OCT) and clinical data

Matthew McLeod; Javid Abderezaei; Yusuke Kikuchi; Chen Chen; Acner Camino Benech; Daniela Ferrara; Neha Anegondi; Qi Yang

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):5645.

ARVO Annual Meeting Abstract June 2024

Deep learning-based optical coherence tomography segmentation of retinal fluids and layers using multi-grader annotations

Sofia Pla Alemany; Thomas Albrecht; Alessandra Valcarcel; Derrek Hibar; Michael H. Chen; Dinah Chen; Vivian Look; Vivide Chang; Daniela Ferrara; Huanxiang Lu

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):2406.

ARVO Annual Meeting Abstract June 2024

Machine learning to predict GA growth rate via clinical and derived autofluorescence imaging features

Julia Cluceru; Ondrej Slama; Neha Anegondi; Simon S. Gao; Daniela Ferrara; Michel Friesenhahn; Christina Rabe

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):2378.

ARVO Annual Meeting Abstract June 2024

Deep learning to identify diffuse retinal thickening (DRT) on optical coherence tomography (OCT)

Dimitrios Damopoulos; Thomas Albrecht; Alessandra Valcarcel; Derrek Hibar; Michael H. Chen; Dinah Chen; Vivian Look; Vivide Chang; Daniela Ferrara; Huanxiang Lu

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):1610.

ARVO Annual Meeting Abstract June 2024

Towards automated optical coherence tomography (OCT) data analysis for a real-world diabetic macular edema (DME) treatment cohort

James Talks; Tunde Peto; Xiaoyong Wang; Anda Gershon; Geeta Menon; Faruque Ghanchi; Xin Chen; Vivian Look; Huanxiang Lu; Michael H. Chen; Daniela Ferrara; Gloria Chi; Qi Yang

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):5956.

Retina November 2023

Imaging Histology Correlations of Intraretinal Fluid in Neovascular Age-Related Macular Degeneration

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Andreas Berlin; Jeffrey D. Messinger; Chandrakumar Balaratnasingam; Randev Mendis; Daniela Ferrara; K. Bailey Freund; Christine A. Curcio
TAGS: diagnostic imaging, exudative age-related macular degeneration, eye, histology, donors, cysts
Trans. Vis. Sci. Tech.. 2023; 12(11):13. https://doi.org/10.1167/tvst.12.11.13

Includes: Supplemental Content

Retina July 2023

Geographic Atrophy Segmentation Using Multimodal Deep Learning

PDF

Theodore Spaide; Jiaxiang Jiang; Jasmine Patil; Neha Anegondi; Verena Steffen; Michael G. Kawczynski; Elizabeth M. Newton; Christina Rabe; Simon S. Gao; Aaron Y. Lee; Frank G. Holz; SriniVas Sadda; Steffen Schmitz-Valckenberg; Daniela Ferrara
TAGS: atrophy, datasets, deep learning, screening, training, diagnostic imaging
Trans. Vis. Sci. Tech.. 2023; 12(7):10. https://doi.org/10.1167/tvst.12.7.10

Includes: Supplemental Content

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Deep Learning-based Image Quality Assessment for Optical Coherence Tomography

Structure-function correlations in GA using AI-based retinal layers lossmeasurements on OCT

The challenging assessment of foveal involvement in geographic atrophy (GA) on spectral-domain optical coherence tomography (SD-OCT)

The impact of multimodal retinal imaging registration for deep-learning segmentation algorithms in geographic atrophy

Repeatability Study for Retinal Optical Coherence Tomography (OCT) Segmentation Algorithms (ROSA) in neovascular age-related macular degeneration (nAMD)

Future optical coherence tomography image generation for anatomical treatment response prediction

Deep learning (DL) to predict faricimab treatment response in diabetic macular edema (DME) using color fundus photos and clinical data

Oral Antioxidant and Lutein Supplements are not Associated with Geographic Atrophy Progression in Age-related Macular Degeneration

Deep Learning Approaches to Predict Geographic Atrophy Progression Using Three-Dimensional OCT Imaging

Clinical and Imaging Characteristics of PRPH2 Retinopathies in a Longitudinal Cohort and Diagnostic Implications

Topographic Clinical Insights From Deep Learning–Based Geographic Atrophy Progression Prediction

Generalizability of foundation models for geographic atrophy (GA) lesion segmentation in fundus autofluorescence (FAF)

Predicting functional outcomes for different treatment durations of faricimab in diabetic macular edema (DME)

Faricimab treatment response prediction in diabetic macular edema (DME) using deep learning on optical coherence tomography (OCT) and clinical data

Deep learning-based optical coherence tomography segmentation of retinal fluids and layers using multi-grader annotations

Machine learning to predict GA growth rate via clinical and derived autofluorescence imaging features

Deep learning to identify diffuse retinal thickening (DRT) on optical coherence tomography (OCT)

Towards automated optical coherence tomography (OCT) data analysis for a real-world diabetic macular edema (DME) treatment cohort

Imaging Histology Correlations of Intraretinal Fluid in Neovascular Age-Related Macular Degeneration

Geographic Atrophy Segmentation Using Multimodal Deep Learning

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