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Retinal Diseases

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Automated Abnormality Detection in Patient Retinal Function: A Deep Learning-Powered Electroretinogram Analysis System.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The electroretinogram (ERG) is an ophthalmic electrophysiology test designed to objectively measure the electrical response of the photoreceptor cells in the human retina. The analysis of the ERG is highly useful in evaluating various retinal disease...

Artificial intelligence in managing retinal disease-current concepts and relevant aspects for health care providers.

Wiener medizinische Wochenschrift (1946)
Given how the diagnosis and management of many ocular and, most specifically, retinal diseases heavily rely on various imaging modalities, the introduction of artificial intelligence (AI) into this field has been a logical, inevitable, and successful...

Efficient diagnosis of retinal disorders using dual-branch semi-supervised learning (DB-SSL): An enhanced multi-class classification approach.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The early diagnosis of retinal disorders is essential in preventing permanent or partial blindness. Identifying these conditions promptly guarantees early treatment and prevents blindness. However, the challenge lies in accurately diagnosing these co...

Anomaly Detection in Retinal OCT Images With Deep Learning-Based Knowledge Distillation.

Translational vision science & technology
PURPOSE: The purpose of this study was to develop a robust and general purpose artificial intelligence (AI) system that allows the identification of retinal optical coherence tomography (OCT) volumes with pathomorphological manifestations not present...

An Intelligent Grading Model for Myopic Maculopathy Based on Long-Tailed Learning.

Translational vision science & technology
PURPOSE: To develop an intelligent grading model for myopic maculopathy based on a long-tail learning framework, using the improved loss function LTBSoftmax. The model addresses the long-tail distribution problem in myopic maculopathy data to provide...

EffiViT: Hybrid CNN-Transformer for Retinal Imaging.

Computers in biology and medicine
The human eye is a vital sensory organ that is crucial for visual perception. The retina is the main component of the eye and is responsible for visual signals. Due to its characteristics, the retina can reveal the occurrence of ocular diseases. So, ...

Global-Local Transformer Network for Automatic Retinal Pathological Fluid Segmentation in Optical Coherence Tomography Images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: As a pivotal biomarker, the accurate segmentation of retinal pathological fluid such as intraretinal fluid (IRF), subretinal fluid (SRF), and pigment epithelial detachment (PED), was a critical task for diagnosis and treatme...

The potential of artificial intelligence reading label system on the training of ophthalmologists in retinal diseases, a multicenter bimodal multi-disease study.

BMC medical education
OBJECTIVE: To assess the potential of artificial intelligence reading label system on the training of ophthalmologists in a multicenter bimodal multi-disease study.

Integrating lightweight convolutional neural network with entropy-informed channel attention and adaptive spatial attention for OCT-based retinal disease classification.

Computers in biology and medicine
This article proposes an effective and lightweight contextual convolutional neural network architecture called LOCT-Net for classifying retinal diseases. The LOCT-Net adopts nested residual blocks to capture the local patterns from the optical cohere...