[Classification of retinal degeneration in children].

Bull Soc Ophtalmol Fr

Published: March 1990

A classification of the hereditary retinal degenerations in childhood is presented. It is based on an histopathologic approach. It includes rods and cones dysfunctions, pigment epithelium degenerations and vitreoretinal degenerations. Each of them is studied according its own clinical, electrophysiologic, evolutive and genetic characteristic features.

Download full-text PDF

Source

Publication Analysis

Top Keywords

[classification retinal
4
retinal degeneration
4
degeneration children]
4
children] classification
4
classification hereditary
4
hereditary retinal
4
retinal degenerations
4
degenerations childhood
4
childhood presented
4
presented based
4

Similar Publications

Purpose: This study aimed to initially test whether machine learning approaches could categorically predict two simple biological features, mouse age and mouse species, using the retinal segmentation metrics.

Methods: The retinal layer thickness data obtained from C57BL/6 and DBA/2J mice were processed for machine learning after segmenting mouse retinal SD-OCT scans. Twenty-two models were trained to predict the mouse groups.

View Article and Find Full Text PDF

A novel non-invasive EEG-SSVEP diagnostic tool for color vision deficiency in individuals with locked-in syndrome.

Front Bioeng Biotechnol

January 2025

Biomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.

Introduction: Color vision deficiency (CVD), a common visual impairment, affects individuals' ability to differentiate between various colors due to malfunctioning or absent color photoreceptors in the retina. Currently available diagnostic tests require a behavioral response, rendering them unsuitable for individuals with limited physical and communication abilities, such as those with locked-in syndrome. This study introduces a novel, non-invasive method that employs brain signals, specifically Steady-State Visually Evoked Potentials (SSVEPs), along with Ishihara plates to diagnose CVD.

View Article and Find Full Text PDF

Diabetic retinopathy (DR) presents a significant concern among diabetic patients, often leading to vision impairment or blindness if left untreated. Traditional diagnosis methods are prone to human error, necessitating accurate alternatives. While various computer-aided systems have been developed to assist in DR detection, there remains a need for accurate and efficient methods to classify its stages.

View Article and Find Full Text PDF

ReIU: an efficient preliminary framework for Alzheimer patients based on multi-model data.

Front Public Health

January 2025

Engineering Research Center of Photoelectric Detection and Perception Technology, Yunnan Normal University, Kunming, China.

The rising incidence of Alzheimer's disease (AD) poses significant challenges to traditional diagnostic methods, which primarily rely on neuropsychological assessments and brain MRIs. The advent of deep learning in medical diagnosis opens new possibilities for early AD detection. In this study, we introduce retinal vessel segmentation methods based on U-Net ad iterative registration Learning (ReIU), which extract retinal vessel maps from OCT angiography (OCT-A) facilities.

View Article and Find Full Text PDF

Aim: To quantify and compare longitudinal thickness changes of the ganglion cell complex (GCC) and the choroid in patients with different patterns of age-related macular degeneration (AMD) progression.

Methods: Retrospective cohort analysis of anonymized data from participants aged 50y or more and diagnosed with early/intermediate AMD in at least one eye (with no evidence of advanced AMD). A total of 64 participants were included from the Instituto de Retina de Lisboa (IRL) study (IPL/2022/MetAllAMD_ESTeSL) and divided into 4 groups according to the Rotterdam classification for AMD.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!