AIMC Topic: Ophthalmoscopy
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Exploiting ensemble learning for automatic cataract detection and grading.
Computer methods and programs in biomedicine
Oct 24, 2015
Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a...
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...
SLOctolyzer: Fully Automatic Analysis Toolkit for Segmentation and Feature Extracting in Scanning Laser Ophthalmoscopy Images.
Translational vision science & technology
Nov 4, 2024
PURPOSE: The purpose of this study was to introduce SLOctolyzer: an open-source analysis toolkit for en face retinal vessels in infrared reflectance scanning laser ophthalmoscopy (SLO) images.
SLO-Net: Enhancing Multiple Sclerosis Diagnosis Beyond Optical Coherence Tomography Using Infrared Reflectance Scanning Laser Ophthalmoscopy Images.
Translational vision science & technology
Jul 1, 2024
PURPOSE: Several machine learning studies have used optical coherence tomography (OCT) for multiple sclerosis (MS) classification with promising outcomes. Infrared reflectance scanning laser ophthalmoscopy (IR-SLO) captures high-resolution fundus ima...
AOSLO-net: A Deep Learning-Based Method for Automatic Segmentation of Retinal Microaneurysms From Adaptive Optics Scanning Laser Ophthalmoscopy Images.
Translational vision science & technology
Aug 1, 2022
PURPOSE: Accurate segmentation of microaneurysms (MAs) from adaptive optics scanning laser ophthalmoscopy (AOSLO) images is crucial for identifying MA morphologies and assessing the hemodynamics inside the MAs. Herein, we introduce AOSLO-net to perfo...
Commentary: Deep learning in retinopathy of prematurity: Where do we stand?
Indian journal of ophthalmology
Apr 1, 2022
EVALUATION OF ARTIFICIAL INTELLIGENCE-BASED QUANTITATIVE ANALYSIS TO IDENTIFY CLINICALLY SIGNIFICANT SEVERE RETINOPATHY OF PREMATURITY.
Retina (Philadelphia, Pa.)
Jan 1, 2022
PURPOSE: To evaluate the screening potential of a deep learning algorithm-derived severity score by determining its ability to detect clinically significant severe retinopathy of prematurity (ROP).
Artificial intelligence for detection of optic disc abnormalities.
Current opinion in neurology
Feb 1, 2020
PURPOSE OF REVIEW: The aim of this review is to highlight novel artificial intelligence-based methods for the detection of optic disc abnormalities, with particular focus on neurology and neuro-ophthalmology.
Translational Retinal Imaging.
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Jan 1, 2020
The diagnosis and treatment of medical retinal disease is now inseparable from retinal imaging in all its multimodal incarnations. The purpose of this article is to present a selection of very different retinal imaging techniques that are truly trans...
Towards Accurate Segmentation of Retinal Vessels and the Optic Disc in Fundoscopic Images with Generative Adversarial Networks.
Journal of digital imaging
Jun 1, 2019
Automatic segmentation of the retinal vasculature and the optic disc is a crucial task for accurate geometric analysis and reliable automated diagnosis. In recent years, Convolutional Neural Networks (CNN) have shown outstanding performance compared ...
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