Search | TVST | ARVO Journals

tvst

Issues
Topics
For Authors
About
- Editorial Board

Journals Home

MANAGE ALERTS

Access Provided By:
MIT Libraries

Forgot password?

Create an Account

To View More...

Purchase this article with an account.

or

Subscribe Now

Issues
Topics
For Authors
About
- Editorial Board

Narrow View

NARROW

Content Type

Meeting Abstract (10)
Journal Articles (3)

Journal

Investigative Ophthalmology & Visual Science (10)
Translational Vision Science & Technology (3)

Article Type

ARVO Annual Meeting Abstract (10)
Articles (2)
Special Issue (1)

Topics

Eye Anatomy and Disorders (3)
Retina (3)
Translational Research (3)
Clinical and Epidemiologic Research (1)
Genetics (1)
Imaging (1)
Multidisciplinary Ophthalmic Imaging (1)
Retinal Imaging (1)

Tags

datasets (2)
mice (2)
training (2)
cell culture techniques (1)
choroid (1)
deferiprone (1)
diagnostic imaging (1)
iron chelating agents (1)
pathology (1)
photoreceptors (1)

Specify Date Range

From: To: Apply

Showing 1 – 13 of 13

SORT: Best Match Most Recent Oldest

VIEW: Basic | Expanded

ARVO Annual Meeting Abstract June 2024

Improving laser targeting accuracy with Augmented Reality guidance in retinal laser therapy

Sangjun (Sarah) Eom; Miroslav Pajic; Maria Gorlatova; Majda Hadziahmetovic

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):793.

ARVO Annual Meeting Abstract June 2024

Binary Classification of OCT Images using the Retina Foundation Model on Limited Data

David Kuo; Qitong Gao; Miroslav Pajic; Majda Hadziahmetovic

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):1616.

ARVO Annual Meeting Abstract June 2024

Evaluating Performance of ResNet-50 and RETFound Image Classification Algorithms on Ultra-widefield Fundus Images

Nikhil Varma Gadiraju; David Kuo; Vahid Ownagh; Terry Lee; Lindsey A Chew; Grant A. Justin; Nita Valikodath; Stephanie Hsu; Miroslav Pajic; Majda Hadziahmetovic; Lejla Vajzovic

Invest. Ophthalmol. Vis. Sci.. 2024; 65(7):1605.

ARVO Annual Meeting Abstract June 2023

Augmented reality for retinal laser therapy

Sangjun (Sarah) Eom; Miroslav Pajic; Maria Gorlatova; Majda Hadziahmetovic

Invest. Ophthalmol. Vis. Sci.. 2023; 64(8):216.

ARVO Annual Meeting Abstract June 2023

Deep learning for longitudinal OCT retinal layer thickness and AMD progression prediction

Qitong Gao; Joshua Amason; Jay Rathinavelu; Miroslav Pajic; Majda Hadziahmetovic

Invest. Ophthalmol. Vis. Sci.. 2023; 64(8):308.

ARVO Annual Meeting Abstract June 2022

An end-to-end deep learning method for predicting retinal layer thickness from Optical Coherence Tomography (OCT) images in patients with clinical progression of Age-related Macular Degeneration (AMD)

Qitong Gao; Joshua Amason; Amanda Del Risco; Praruj Pant; Terry Lee; Justin Ma; Jennifer Minjia Chang-Wolf; Jay Rathinavelu; Aditya Kotla; Miroslav Pajic; Majda Hadziahmetovic

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):3008 – F0278.

ARVO Annual Meeting Abstract June 2022

Exploring Deep-Learning on SD-OCT images as an Effective Mitigation Technique for Hydroxychloroquine-Induced Retinal Toxicity

Harsh Bandhey; Amanda Del Risco; Qitong Gao; Jay Rathinavelu; Miroslav Pajic; Majda Hadziahmetovic

Invest. Ophthalmol. Vis. Sci.. 2022; 63(7):3330 – F0139.

ARVO Annual Meeting Abstract June 2021

Deep learning approach for automated detection of retinal pathology from ultra-widefield retinal images

Mingzhe Hu; Joshua Amason; Terry Lee; Qitong Gao; Durga Borkar; Miroslav Pajic; Majda Hadziahmetovic

Invest. Ophthalmol. Vis. Sci.. 2021; 62(8):2129.

ARVO Annual Meeting Abstract June 2021

A deep learning-based automated tool for the identification of referable retinal pathology from multi-modal imaging sources

Qitong Gao; Joshua Amason; Scott Cousins; Miroslav Pajic; Majda Hadziahmetovic

Invest. Ophthalmol. Vis. Sci.. 2021; 62(8):2128.

Articles May 2021

Automated Identification of Referable Retinal Pathology in Teleophthalmology Setting

PDF

Qitong Gao; Joshua Amason; Scott Cousins; Miroslav Pajic; Majda Hadziahmetovic
TAGS: datasets, pathology, training, diagnostic imaging
Trans. Vis. Sci. Tech.. 2021; 10(6):30. https://doi.org/10.1167/tvst.10.6.30

Includes: Supplemental Content

Special Issue June 2020

Automated Recognition of Retinal Pigment Epithelium Cells on Limited Training Samples Using Neural Networks

PDF

Qitong Gao; Ying Xu; Joshua Amason; Anna Loksztejn; Scott Cousins; Miroslav Pajic; Majda Hadziahmetovic
TAGS: retinal pigment cell, retinal pigment epithelium, training, cell culture techniques, datasets, mice, choroid
Trans. Vis. Sci. Tech.. 2020; 9(2):31. https://doi.org/10.1167/tvst.9.2.31

Includes: Supplemental Content

ARVO Annual Meeting Abstract June 2020

Deep Learning Approach for Automated Recognition of Retinal Pigment Epithelium Cell

Majda Hadziahmetovic; Qitong Gao; Ying Xu; Joshua Amason; Anna Loksztejn; Scott W Cousins; Miroslav Pajic

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2030.

Articles October 2012

The Oral Iron Chelator Deferiprone Protects Against Retinal Degeneration Induced through Diverse Mechanisms

PDF

Majda Hadziahmetovic; Miroslav Pajic; Steven Grieco; Ying Song; Delu Song; Yafeng Li; Alyssa Cwanger; Jared Iacovelli; Sally Chu; Gui-shuang Ying; John Connelly; Michael Spino; Joshua L Dunaief
TAGS: deferiprone, iron chelating agents, retinal degeneration, mice, photoreceptors, retina
Trans. Vis. Sci. Tech.. 2012; 1(3):2. https://doi.org/10.1167/tvst.1.3.2

« Previous

Advertisement

Follow @ARVOtvst

TVST Home
Issues
Topics
For Authors

About
- Editorial Board

Online ISSN: 2164-2591

Investigative Ophthalmology & Visual Science
Journal of Vision
Translational Vision Science & Technology

JOURNALS HOME
TOPICS
ABOUT ARVO JOURNALS

Copyright © 2025 Association for Research in Vision and Ophthalmology.

Access Provided By:
MIT Libraries

Forgot password?

To View More...

Purchase this article with an account.

Create an Account

or

Subscribe Now

×

×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

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

×

This site uses cookies. By continuing to use our website, you are agreeing to our privacy policy.Accept