AIMC Topic: Fluorescein Angiography
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A MULTITASK DEEP-LEARNING SYSTEM FOR ASSESSMENT OF DIABETIC MACULAR ISCHEMIA ON OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IMAGES.
Retina (Philadelphia, Pa.)
Jan 1, 2022
PURPOSE: We aimed to develop and test a deep-learning system to perform image quality and diabetic macular ischemia (DMI) assessment on optical coherence tomography angiography (OCTA) images.
An Open-Source Deep Learning Network for Reconstruction of High-Resolution OCT Angiograms of Retinal Intermediate and Deep Capillary Plexuses.
Translational vision science & technology
Nov 1, 2021
PURPOSE: We propose a deep learning-based image reconstruction algorithm to produce high-resolution optical coherence tomographic angiograms (OCTA) of the intermediate capillary plexus (ICP) and deep capillary plexus (DCP).
IMPACT OF RESIDUAL SUBRETINAL FLUID VOLUMES ON TREATMENT OUTCOMES IN A SUBRETINAL FLUID-TOLERANT TREAT-AND-EXTEND REGIMEN.
Retina (Philadelphia, Pa.)
Nov 1, 2021
PURPOSE: To investigate associations between residual subretinal fluid (rSRF) volumes, quantified using artificial intelligence and treatment outcomes in a subretinal fluid (SRF)-tolerant treat-and-extend (T&E) regimen in neovascular age-related macu...
Subretinal Fluid
Drug Tolerance
Visual Acuity
Tomography, Optical Coherence
Fundus Oculi
Prospective Studies
Vascular Endothelial Growth Factor A
Angiogenesis Inhibitors
Intravitreal Injections
Treatment Outcome
Fluorescein Angiography
Follow-Up Studies
Ranibizumab
Wet Macular Degeneration
Humans
Artificial Intelligence
Artificial intelligence-based predictions in neovascular age-related macular degeneration.
Current opinion in ophthalmology
Sep 1, 2021
PURPOSE OF REVIEW: Predicting treatment response and optimizing treatment regimen in patients with neovascular age-related macular degeneration (nAMD) remains challenging. Artificial intelligence-based tools have the potential to increase confidence ...
Automated deep learning in ophthalmology: AI that can build AI.
Current opinion in ophthalmology
Sep 1, 2021
PURPOSE OF REVIEW: The purpose of this review is to describe the current status of automated deep learning in healthcare and to explore and detail the development of these models using commercially available platforms. We highlight key studies demons...
IMAGE EVALUATION OF ARTIFICIAL INTELLIGENCE-SUPPORTED OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IMAGING USING OCT-A1 DEVICE IN DIABETIC RETINOPATHY.
Retina (Philadelphia, Pa.)
Aug 1, 2021
PURPOSE: To investigate the effect of denoise processing by artificial intelligence (AI) on the optical coherence tomography angiography (OCTA) images in eyes with retinal lesions.
Macular Ischemia Quantification Using Deep-Learning Denoised Optical Coherence Tomography Angiography in Branch Retinal Vein Occlusion.
Translational vision science & technology
Jun 1, 2021
PURPOSE: To examine whether deep-learning denoised optical coherence tomography angiography (OCTA) images could enhance automated macular ischemia quantification in branch retinal vein occlusion (BRVO).
Imaging Biomarkers of 1-Year Activity in Type 1 Macular Neovascularization.
Translational vision science & technology
May 3, 2021
PURPOSE: The purpose of this study was to evaluate the predictive value of optical coherence tomography (OCT) and OCT angiography (OCTA) parameters at baseline on lesion's activity at the 1-year follow-up in type 1 macular neovascularizations (MNVs) ...
Deep Learning Detection of Sea Fan Neovascularization From Ultra-Widefield Color Fundus Photographs of Patients With Sickle Cell Hemoglobinopathy.
JAMA ophthalmology
Feb 1, 2021
IMPORTANCE: Adherence to screening for vision-threatening proliferative sickle cell retinopathy is limited among patients with sickle cell hemoglobinopathy despite guidelines recommending dilated fundus examinations beginning in childhood. An automat...
Photography
Retinal Neovascularization
Retrospective Studies
Retinal Vessels
Female
Observer Variation
Reproducibility of Results
Deep Learning
Humans
Pattern Recognition, Automated
Young Adult
Adult
Predictive Value of Tests
Fluorescein Angiography
Anemia, Sickle Cell
Cross-Sectional Studies
Image Interpretation, Computer-Assisted
Male
Middle Aged
SWEPT SOURCE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY, FLUORESCEIN ANGIOGRAPHY, AND INDOCYANINE GREEN ANGIOGRAPHY COMPARISONS REVISITED: Using a Novel Deep-Learning-Assisted Approach for Image Registration.
Retina (Philadelphia, Pa.)
Oct 1, 2020
PURPOSE: To compare area measurements between swept source optical coherence tomography angiography (SSOCTA), fluorescein angiography (FA), and indocyanine green angiography (ICGA) after applying a novel deep-learning-assisted algorithm for accurate ...
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