AIMC Topic: Retinal Hemorrhage
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Haemorrhage diagnosis in colour fundus images using a fast-convolutional neural network based on a modified U-Net.
Network (Bristol, England)
Feb 12, 2024
Retinal haemorrhage stands as an early indicator of diabetic retinopathy, necessitating accurate detection for timely diagnosis. Addressing this need, this study proposes an enhanced machine-based diagnostic test for diabetic retinopathy through an u...
Deep Learning Approach for Differentiating Etiologies of Pediatric Retinal Hemorrhages: A Multicenter Study.
International journal of molecular sciences
Oct 12, 2023
Retinal hemorrhages in pediatric patients can be a diagnostic challenge for ophthalmologists. These hemorrhages can occur due to various underlying etiologies, including abusive head trauma, accidental trauma, and medical conditions. Accurate identif...
Beyond the : Deep Learning Shows Promise in the Detection of Retinal Hemorrhage on Pediatric Head CT.
AJR. American journal of roentgenology
Aug 23, 2023
Deep Learning for Localized Detection of Optic Disc Hemorrhages.
American journal of ophthalmology
Jul 23, 2023
PURPOSE: To develop an automated deep learning system for detecting the presence and location of disc hemorrhages in optic disc photographs.
Development of a Deep Learning Model for Retinal Hemorrhage Detection on Head Computed Tomography in Young Children.
JAMA network open
Jun 1, 2023
IMPORTANCE: Abusive head trauma (AHT) in children is often missed in medical encounters, and retinal hemorrhage (RH) is considered strong evidence for AHT. Although head computed tomography (CT) is obtained routinely, all but exceptionally large RHs ...
First-in-Human Robot-Assisted Subretinal Drug Delivery Under Local Anesthesia.
American journal of ophthalmology
Nov 14, 2021
PURPOSE: To report the results of a first-in-human study using a robotic device to assist subretinal drug delivery in patients undergoing vitreoretinal surgery for macular hemorrhage.
Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software.
Current eye research
May 15, 2020
: To describe the development and validation of an artificial intelligence-based, deep learning algorithm (DeepDR) for the detection of diabetic retinopathy (DR) in retinal fundus photographs. : Five hundred fundus images, which had detailed labellin...
Development and Evaluation of a Deep Learning System for Screening Retinal Hemorrhage Based on Ultra-Widefield Fundus Images.
Translational vision science & technology
Jan 29, 2020
PURPOSE: To develop and evaluate a deep learning (DL) system for retinal hemorrhage (RH) screening using ultra-widefield fundus (UWF) images.
New grading criterion for retinal haemorrhages in term newborns based on deep convolutional neural networks.
Clinical & experimental ophthalmology
Nov 11, 2019
BACKGROUND: To define a new quantitative grading criterion for retinal haemorrhages in term newborns based on the segmentation results of a deep convolutional neural network.
Fundus images analysis using deep features for detection of exudates, hemorrhages and microaneurysms.
BMC ophthalmology
Nov 6, 2018
BACKGROUND: Convolution neural networks have been considered for automatic analysis of fundus images to detect signs of diabetic retinopathy but suffer from low sensitivity.
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