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Articles February 2021

Determining the Location of the Fovea Centralis Via En-Face SLO and Cross-Sectional OCT Imaging in Patients Without Retinal Pathology

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Archana A. Nair; Rebecca Liebenthal; Shefali Sood; Grant L. Hom; Marc E. Ohlhausen; Thais F. Conti; Carolina C. S. Valentim; Hiroshi Ishikawa; Gadi Wollstein; Joel S. Schuman; Rishi P. Singh; Yasha S. Modi
TAGS: diagnostic imaging, face, fovea centralis, pathology, scanning laser ophthalmoscopy, eye, optic disk
Trans. Vis. Sci. Tech.. 2021; 10(2):25. doi: https://doi.org/10.1167/tvst.10.2.25

ARVO Imaging in the Eye Conference Abstract July 2020

Visible-Light OCT Captures In-vivo Changes in Retinal Oximetry in Ischemic Retinal Diseases

Jonathan Kfir; Zeinab Ghassabi; Mengfei Wu; Ian Rubinoff; Roman V. Kuranov; Yuanbo Wang; benjamin Davis; Behnam Tayebi; Joel Schuman; Hao Zhang; Hiroshi Ishikawa; Gadi Wollstein

Invest. Ophthalmol. Vis. Sci.. 2020; 61(9):PB00111. doi:

ARVO Imaging in the Eye Conference Abstract July 2020

Can We Predict the Location of Glaucoma Progression Based on the Location of the Largest Peripapillary Atrophy?

Alexi Geevarghese; Fabio Lavinsky; Hiroshi Ishikawa; Mengfei Wu; Mengling Liu; Jenna Tauber; Joseph Panarelli; Assumpta Madu; Joel Schuman; Gadi Wollstein

Invest. Ophthalmol. Vis. Sci.. 2020; 61(9):PB00122. doi:

ARVO Imaging in the Eye Conference Abstract July 2020

Spatial association of longitudinal vessel density with visual fields

Maria de los Angeles Ramos Cadena; Gadi Wollstein; Mengfei Wu; Mengling Liu; Rebecca Liebenthal; Hiroshi Ishikawa; Joel Schuman

Invest. Ophthalmol. Vis. Sci.. 2020; 61(9):PB00138. doi:

ARVO Imaging in the Eye Conference Abstract July 2020

Improved Denoising of Optical Coherence Tomography via Repeated Acquisitions and Unsupervised Deep Learning

Guillaume Gisbert; Neel Dey; Hiroshi Ishikawa; Joel Schuman; James Fishbaugh; Guido Gerig

Invest. Ophthalmol. Vis. Sci.. 2020; 61(9):PB0035. doi:

ARVO Imaging in the Eye Conference Abstract July 2020

Determining retinal nerve fiber layer thickness vulnerability zones in mild glaucoma with rescaled optic nerve heads

Raymond C S Wong; Mikhail Startsev; Yangjiani Li; Eun Young Choi; Dian Li; Lucy Shen; Louis Pasquale; Gadi Wollstein; Hiroshi Ishikawa; Joel Schuman; Mengyu Wang; Tobias Elze

Invest. Ophthalmol. Vis. Sci.. 2020; 61(9):PB005. doi:

ARVO Imaging in the Eye Conference Abstract July 2020

Using hierarchical cluster analysis to cluster 52 visual field points

Mengfei Wu; Mengling Liu; Hiroshi Ishikawa; Joel Schuman; Gadi Wollstein

Invest. Ophthalmol. Vis. Sci.. 2020; 61(9):PB0052. doi:

ARVO Imaging in the Eye Conference Abstract July 2020

In-Vivo 3D Lamina Cribrosa Microstructure Characterization of Healthy Non-Human Primates

Yoav Glidai; Anoop Sainulabdeen; Mengfei Wu; Matthew A. Smith; Ian A. Sigal; Hiroshi Ishikawa; Joel Schuman; Gadi Wollstein

Invest. Ophthalmol. Vis. Sci.. 2020; 61(9):PP004. doi:

ARVO Annual Meeting Abstract June 2020

Social roles in addition to daily activities are factors associated with function in glaucoma

Heather Livengood; Gadi Wollstein; Hiroshi Ishikawa; Mengfei Wu; Joel S Schuman

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):1570. doi:

ARVO Annual Meeting Abstract June 2020

β zone Peripapillary Atrophy as a Predictor of Glaucomatous Structural and Functional Progression

Alexi Geevarghese; Fabio Lavinsky; Hiroshi Ishikawa; Mengfei Wu; Mengling Liu; Jenna Tauber; Joseph Panarelli; Assumpta A. Madu; Joel S Schuman; Gadi Wollstein

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):3211. doi:

ARVO Annual Meeting Abstract June 2020

Determining aligned retinal nerve fiber layer thickness (RNFLT) vulnerability zones in mild glaucoma

Raymond C S Wong; Mikhail Startsev; Yangjiani Li; Eun Young Choi; Dian Li; Lucy Shen; Louis R Pasquale; Gadi Wollstein; Hiroshi Ishikawa; Joel S Schuman; Mengyu Wang; Tobias Elze

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):1970. doi:

ARVO Annual Meeting Abstract June 2020

Longitudinal Changes in the Macula and Optic Nerve in Familial Dysautonomia

Jonathan Kfir; Mengfei Wu; Mengling Liu; Leela Raju; Joel S Schuman; Hiroshi Ishikawa; M. Isabel Vanegas; Carlos Mendonza-Santiesteban; Jose Alberto Palma; Lucy Norcliffe-Kaufmann; Barr Morgenstein; Horacio Kaufmann; Gadi Wollstein

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2145. doi:

ARVO Annual Meeting Abstract June 2020

Under the Surface: Deformations in the Deep Lamina Cribrosa

Yoav Glidai; Mengfei Wu; Joel S Schuman; Katie Lucy; Ian A Sigal; Matthew A Smith; Hiroshi Ishikawa; Gadi Wollstein

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):3529. doi:

ARVO Annual Meeting Abstract June 2020

Can Clock Hour OCT Retinal Nerve Fiber Layer (RNFL) Thickness Measurements Outperform Global Mean RNFL for Glaucoma Diagnosis?

Mengfei Wu; Mengling Liu; Joel S Schuman; Hiroshi Ishikawa; Gadi Wollstein

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):5195. doi:

ARVO Annual Meeting Abstract June 2020

Using Deep Learning Methods to Develop a Novel Predictive Glaucoma Progression Model

Andrew Lin; David Fenyo; Joel S Schuman; Gadi Wollstein; Hiroshi Ishikawa

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):872. doi:

ARVO Annual Meeting Abstract June 2020

Deep learning network for Glaucoma detection at 40 million voxels

Bhavna Josephine Antony; Hiroshi Ishikawa; Gadi Wollstein; Joel S Schuman; Rahil Garnavi

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):4528. doi:

ARVO Annual Meeting Abstract June 2020

Predicting Macular Progression Map Using Deep Learning

Zhiqi Chen; Yao Wang; María de los Angeles Ramos-Cadena; Gadi Wollstein; Joel S Schuman; Hiroshi Ishikawa

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):4532. doi:

ARVO Annual Meeting Abstract June 2020

Estimating visual field progression rates of glaucoma patients using estimates derived from OCT scans

Hsin-Hao Yu; Bhavna Josephine Antony; Hiroshi Ishikawa; Gadi Wollstein; Joel S Schuman; Rahil Garnavi

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):875. doi:

ARVO Annual Meeting Abstract June 2020

Understanding Deep Learning Decision for Glaucoma Detection using 3D Volumes

Yasmeen Mourice George; Bhavna J. Antony; Hiroshi Ishikawa; Gadi Wollstein; Joel S Schuman; Rahil Garnavi

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2022. doi:

ARVO Annual Meeting Abstract June 2020

Spectral calibration techniques for clinical retinal oximetry with visible-light optical coherence tomography

Ian Rubinoff; Roman V. Kuranov; Yuanbo Wang; Amani A Fawzi; Zeinab Ghassabi; Benjamin Davis; Behnam Tayebi; Gadi Wollstein; Hiroshi Ishikawa; Joel S Schuman; Hao Zhang

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2533. doi:

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Determining the Location of the Fovea Centralis Via En-Face SLO and Cross-Sectional OCT Imaging in Patients Without Retinal Pathology

Visible-Light OCT Captures In-vivo Changes in Retinal Oximetry in Ischemic Retinal Diseases

Can We Predict the Location of Glaucoma Progression Based on the Location of the Largest Peripapillary Atrophy?

Spatial association of longitudinal vessel density with visual fields

Improved Denoising of Optical Coherence Tomography via Repeated Acquisitions and Unsupervised Deep Learning

Determining retinal nerve fiber layer thickness vulnerability zones in mild glaucoma with rescaled optic nerve heads

Using hierarchical cluster analysis to cluster 52 visual field points

In-Vivo 3D Lamina Cribrosa Microstructure Characterization of Healthy Non-Human Primates

Social roles in addition to daily activities are factors associated with function in glaucoma

β zone Peripapillary Atrophy as a Predictor of Glaucomatous Structural and Functional Progression

Determining aligned retinal nerve fiber layer thickness (RNFLT) vulnerability zones in mild glaucoma

Longitudinal Changes in the Macula and Optic Nerve in Familial Dysautonomia

Under the Surface: Deformations in the Deep Lamina Cribrosa

Can Clock Hour OCT Retinal Nerve Fiber Layer (RNFL) Thickness Measurements Outperform Global Mean RNFL for Glaucoma Diagnosis?

Using Deep Learning Methods to Develop a Novel Predictive Glaucoma Progression Model

Deep learning network for Glaucoma detection at 40 million voxels

Predicting Macular Progression Map Using Deep Learning

Estimating visual field progression rates of glaucoma patients using estimates derived from OCT scans

Understanding Deep Learning Decision for Glaucoma Detection using 3D Volumes

Spectral calibration techniques for clinical retinal oximetry with visible-light optical coherence tomography

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