AIMC Topic: Ophthalmoscopes

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Accuracy and Time Comparison Between Side-by-Side and Artificial Intelligence Overlayed Images.

Ophthalmic surgery, lasers & imaging retina Feb 1, 2023
BACKGROUND AND OBJECTIVE: The purpose of this study was to evaluate the accuracy and the time to find a lesion, taken in different platforms, color fundus photographs and infrared scanning laser ophthalmoscope images, using the traditional side-by-si...
Fundus Oculi Ophthalmoscopes Physical Examination Humans Artificial Intelligence
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Cross-Camera External Validation for Artificial Intelligence Software in Diagnosis of Diabetic Retinopathy.

Journal of diabetes research Mar 9, 2022
AIMS: To investigate the applicability of deep learning image assessment software VeriSee DR to different color fundus cameras for the screening of diabetic retinopathy (DR).
Chi-Square Distribution Ophthalmoscopes Software Design Middle Aged Diabetes Mellitus Humans Adult Reproducibility of Results Diabetic Retinopathy Male Artificial Intelligence Female
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Detection of Diabetic Retinopathy from Ultra-Widefield Scanning Laser Ophthalmoscope Images: A Multicenter Deep Learning Analysis.

Ophthalmology. Retina Feb 1, 2021
PURPOSE: To develop a deep learning (DL) system that can detect referable diabetic retinopathy (RDR) and vision-threatening diabetic retinopathy (VTDR) from images obtained on ultra-widefield scanning laser ophthalmoscope (UWF-SLO).
Neural Networks, Computer Female Cross-Sectional Studies Humans Diabetic Retinopathy Deep Learning ROC Curve Equipment Design Male Middle Aged Ophthalmoscopy Ophthalmoscopes
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Artificial Intelligence for Automated Overlay of Fundus Camera and Scanning Laser Ophthalmoscope Images.

Translational vision science & technology Oct 20, 2020
PURPOSE: The purpose of this study was to evaluate the ability to align two types of retinal images taken on different platforms; color fundus (CF) photographs and infrared scanning laser ophthalmoscope (IR SLO) images using mathematical warping and ...
Artificial Intelligence Fundus Oculi Fluorescein Angiography Ophthalmoscopes Lasers Humans
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AMD-GAN: Attention encoder and multi-branch structure based generative adversarial networks for fundus disease detection from scanning laser ophthalmoscopy images.

Neural networks : the official journal of the International Neural Network Society Sep 17, 2020
The scanning laser ophthalmoscopy (SLO) has become an important tool for the determination of peripheral retinal pathology, in recent years. However, the collected SLO images are easily interfered by the eyelash and frame of the devices, which heavil...
Ophthalmoscopes Lasers Ophthalmoscopy Humans Image Processing, Computer-Assisted Neural Networks, Computer Fundus Oculi
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Automatic Segmentation of Retinal Capillaries in Adaptive Optics Scanning Laser Ophthalmoscope Perfusion Images Using a Convolutional Neural Network.

Translational vision science & technology Jul 23, 2020
PURPOSE: Adaptive optics scanning laser ophthalmoscope (AOSLO) capillary perfusion images can possess large variations in contrast, intensity, and background signal, thereby limiting the use of global or adaptive thresholding techniques for automatic...
Capillaries Perfusion Humans Lasers Ophthalmoscopes Neural Networks, Computer
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Deep compressed multichannel adaptive optics scanning light ophthalmoscope.

Science advances May 9, 2025
Adaptive optics scanning light ophthalmoscopy (AOSLO) reveals individual retinal cells and their function, microvasculature, and micropathologies in vivo. As compared to the single-channel offset pinhole and two-channel split-detector nonconfocal AOS...
Ophthalmoscopy Image Processing, Computer-Assisted Humans Optics and Photonics Machine Learning Ophthalmoscopes Retina
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Deep-learning Classifier With an Ultrawide-field Scanning Laser Ophthalmoscope Detects Glaucoma Visual Field Severity.

Journal of glaucoma Jul 1, 2018
PURPOSE: To evaluate the accuracy of detecting glaucoma visual field defect severity using deep-learning (DL) classifier with an ultrawide-field scanning laser ophthalmoscope.
Vision Disorders Image Interpretation, Computer-Assisted Visual Field Tests Ophthalmoscopes Visual Fields Reproducibility of Results Deep Learning Aged Microscopy, Confocal Humans Middle Aged Retrospective Studies Cross-Sectional Studies Glaucoma Severity of Illness Index Female Adult Intraocular Pressure Sensitivity and Specificity Male
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