Search | IOVS | ARVO Journals

Showing 1 – 20 of 27

SORT: Best Match Most Recent Oldest

VIEW: Basic | Expanded

Articles January 2021

Predicting Age From Optical Coherence Tomography Scans With Deep Learning

PDF

Leonardo S. Shigueoka; Eduardo B. Mariottoni; Atalie C. Thompson; Alessandro A. Jammal; Vital P. Costa; Felipe A. Medeiros

Trans. Vis. Sci. Tech.. 2021; 10(1):12. doi: https://doi.org/10.1167/tvst.10.1.12

Glaucoma November 2020

The Effect of Age on Increasing Susceptibility to Retinal Nerve Fiber Layer Loss in Glaucoma

PDF

Alessandro A. Jammal; Samuel I. Berchuck; Atalie C. Thompson; Vital P. Costa; Felipe A. Medeiros

Invest. Ophthalmol. Vis. Sci.. 2020; 61(13):8. doi: https://doi.org/10.1167/iovs.61.13.8

Includes: Supplemental Content

Special Issue July 2020

A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression

PDF

Atalie C. Thompson; Alessandro A. Jammal; Felipe A. Medeiros
TAGS: deep learning, glaucoma, screening
Trans. Vis. Sci. Tech.. 2020; 9(2):42. doi: https://doi.org/10.1167/tvst.9.2.42

ARVO Annual Meeting Abstract June 2020

The relationship between concomitant mental health disorders and disease severity among glaucoma patients

Samuel Berchuck; Alessandro A Jammal; Eduardo Bicalho Mariottoni; Sayan Mukherjee; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):1994. doi:

ARVO Annual Meeting Abstract June 2020

Visual Crowding in Glaucoma: Structural and Functional Relationships

James Stringham; Alessandro A Jammal; Eduardo Bicalho Mariottoni; Tais Estrela; Carla Urata; Leonardo Shigueoka; Nara Ogata; Henry Tseng; Felipe Medeiros

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):3214. doi:

ARVO Annual Meeting Abstract June 2020

From Machine to the Real World: Assessing the Accuracy of a Machine-to-Machine (M2M) Deep Learning Model to Detect Glaucoma during a Population-Based Screening Effort in Brazil

Tais Estrela; Eduardo Bicalho Mariottoni; Tabatta Graciolli; Nubia Chouchounova; Nara Ogata; Mariana Siqueira; Carla Urata; Leonardo Shigueoka; Alessandro A Jammal; Atalie C. Thompson; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):4539. doi:

ARVO Annual Meeting Abstract June 2020

The Effect of Intraocular Pressure Control on Rates of Glaucomatous Structural Loss in a Large Clinical Population

Alessandro A Jammal; Eduardo Bicalho Mariottoni; Atalie C. Thompson; Samuel Berchuck; Tais Estrela; Leonardo Shigueoka; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):5196. doi:

ARVO Annual Meeting Abstract June 2020

The association between race and longitudinal visual field variability

Brian Stagg; Eduardo Mariottoni; Samuel Berchuck; Alessandro A Jammal; Rachel Hess; Kensaku Kawamoto; Ben Haaland; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):4045. doi:

ARVO Annual Meeting Abstract June 2020

Predicting Future Rates of Retinal Nerve Fiber Layer Loss from Deep Learning Assessment of Baseline Optic Disc Photographs

Atalie C. Thompson; Alessandro A Jammal; Eduardo Bicalho Mariottoni; Leonardo Shigueoka; Tais Estrela; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):4533. doi:

ARVO Annual Meeting Abstract June 2020

Effect of diabetes control on rates of visual field loss in patients with glaucoma.

Nicholas Johnson; Alessandro Adad Jammal; Felipe A Medeiros; Leonardo Shigueoka; Eduardo Mariottoni

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):3891. doi:

ARVO Annual Meeting Abstract June 2020

A Deep Learning-Based Mapping of Structure to Function in Glaucoma

Eduardo Bicalho Mariottoni; Shounak Datta; David Dov; Alessandro Adad Jammal; Samuel Berchuck; Ivan Tavares; Lawrence Carin; Felipe Medeiros

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):3213. doi:

Special Issue March 2020

Artificial Intelligence Mapping of Structure to Function in Glaucoma

PDF

Eduardo B. Mariottoni; Shounak Datta; David Dov; Alessandro A. Jammal; Samuel I. Berchuck; Ivan M. Tavares; Lawrence Carin; Felipe A. Medeiros
TAGS: artificial intelligence, glaucoma, retinal nerve fiber layer, visual field defects, spectral domain-optical coherence tomography
Trans. Vis. Sci. Tech.. 2020; 9(2):19. doi: https://doi.org/10.1167/tvst.9.2.19

Includes: Supplemental Content

ARVO Annual Meeting Abstract July 2019

Repeatability of Macular and Optic Nerve Head OCT Parameters In Advanced Glaucoma

Alexandre S C Reis; Alessandro A Jammal; Camila Zangalli; Bruna Gil Ferreira; Jayme R Vianna; Paul H Artes; Vital P Costa

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):1423. doi:

ARVO Annual Meeting Abstract July 2019

Deep Learning Segmentation-Free Assessment of Retinal Nerve Fiber Layer in OCT Scans

Eduardo Bicalho Mariottoni; Alessandro A Jammal; Carla Urata; Atalie C. Thompson; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):1508. doi:

ARVO Annual Meeting Abstract July 2019

A Deep Learning Algorithm can Predict Retinal Nerve Fiber Layer Thickness with Lower Long-term Variability than Conventional Automated Segmentation

Carla Urata; Eduardo Bicalho Mariottoni; Alessandro A Jammal; Atalie C. Thompson; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):1517. doi:

ARVO Annual Meeting Abstract July 2019

The Relationship Between Machine Learning-Derived Binocular Patterns of Visual Field Loss and Patient-Reported Disability in Glaucoma

Nara Ogata; Alessandro A Jammal; Eduardo Bicalho Mariottoni; Carla Urata; Susan Wakil; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):2440. doi:

ARVO Annual Meeting Abstract July 2019

The Relationship between Asymmetries of Corneal Properties and Rates of Visual Field Progression in Glaucoma Patients

Tais Estrela; Alessandro A Jammal; Eduardo Bicalho Mariottoni; Carla Urata; Nara Ogata; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):6199. doi:

ARVO Annual Meeting Abstract July 2019

A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss from Optic Disc Photographs

Atalie C. Thompson; Alessandro A Jammal; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):5577. doi:

ARVO Annual Meeting Abstract July 2019

Detecting Retinal Nerve Fiber Layer Segmentation Errors on Spectral Domain-Optical Coherence Tomography with a Deep Learning Algorithm

Alessandro A Jammal; Atalie C. Thompson; Nara Ogata; Eduardo Bicalho Mariottoni; Carla Urata; Vital P Costa; Felipe A Medeiros

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):2209. doi:

ARVO Annual Meeting Abstract July 2019

Ophthalmological Care and Eyeglasses Distribution in Brazil's Countryside: Descriptive and Epidemiological Data of Nearly Five Thousand Patients

Bruna Gil Ferreira; Ralf Henrique Frinzi Toenjes; Pedro Ivo Garcia de Sousa; Victor Luiz de Paula Souza; Guibson Trindade Torres; Matheus Ivan Schmitz Vieira; Alessandro A Jammal; Priscila Hae Hyun Rim; Monica Alves

Invest. Ophthalmol. Vis. Sci.. 2019; 60(9):4453. doi:

1 2

Next 20 Results »

NARROW

Content Type

Journal

Article Type

Topics

Tags

Specify Date Range

Predicting Age From Optical Coherence Tomography Scans With Deep Learning

The Effect of Age on Increasing Susceptibility to Retinal Nerve Fiber Layer Loss in Glaucoma

A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression

The relationship between concomitant mental health disorders and disease severity among glaucoma patients

Visual Crowding in Glaucoma: Structural and Functional Relationships

From Machine to the Real World: Assessing the Accuracy of a Machine-to-Machine (M2M) Deep Learning Model to Detect Glaucoma during a Population-Based Screening Effort in Brazil

The Effect of Intraocular Pressure Control on Rates of Glaucomatous Structural Loss in a Large Clinical Population

The association between race and longitudinal visual field variability

Predicting Future Rates of Retinal Nerve Fiber Layer Loss from Deep Learning Assessment of Baseline Optic Disc Photographs

Effect of diabetes control on rates of visual field loss in patients with glaucoma.

A Deep Learning-Based Mapping of Structure to Function in Glaucoma

Artificial Intelligence Mapping of Structure to Function in Glaucoma

Repeatability of Macular and Optic Nerve Head OCT Parameters In Advanced Glaucoma

Deep Learning Segmentation-Free Assessment of Retinal Nerve Fiber Layer in OCT Scans

A Deep Learning Algorithm can Predict Retinal Nerve Fiber Layer Thickness with Lower Long-term Variability than Conventional Automated Segmentation

The Relationship Between Machine Learning-Derived Binocular Patterns of Visual Field Loss and Patient-Reported Disability in Glaucoma

The Relationship between Asymmetries of Corneal Properties and Rates of Visual Field Progression in Glaucoma Patients

A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss from Optic Disc Photographs

Detecting Retinal Nerve Fiber Layer Segmentation Errors on Spectral Domain-Optical Coherence Tomography with a Deep Learning Algorithm

Ophthalmological Care and Eyeglasses Distribution in Brazil's Countryside: Descriptive and Epidemiological Data of Nearly Five Thousand Patients

To View More...

You must be signed into an individual account to use this feature.