AIMC Topic: Retina

Clear Filters Showing 121 to 130 of 482 articles

Recognition of diabetic retinopathy and macular edema using deep learning.

Medical & biological engineering & computing
Diabetic retinopathy (DR) and diabetic macular edema (DME) are both serious eye conditions associated with diabetes and if left untreated, and they can lead to permanent blindness. Traditional methods for screening these conditions rely on manual ima...

Autonomous artificial intelligence versus teleophthalmology for diabetic retinopathy.

European journal of ophthalmology
To assess the role of artificial intelligence (AI) based automated software for detection of Diabetic Retinopathy (DR) compared with the evaluation of digital retinography by two double masked retina specialists. Two-hundred one patients (mean age ...

Optimizing Image Enhancement: Feature Engineering for Improved Classification in AI-Assisted Artificial Retinas.

Sensors (Basel, Switzerland)
Artificial retinas have revolutionized the lives of many blind people by enabling their ability to perceive vision via an implanted chip. Despite significant advancements, there are some limitations that cannot be ignored. Presenting all objects capt...

A new intelligent system based deep learning to detect DME and AMD in OCT images.

International ophthalmology
Optical Coherence Tomography (OCT) is widely recognized as the leading modality for assessing ocular retinal diseases, playing a crucial role in diagnosing retinopathy while maintaining a non-invasive modality. The increasing volume of OCT images und...

Model-free robust motion control for biological optical microscopy using time-delay estimation with an adaptive RBFNN compensator.

ISA transactions
The field of large numerical aperture microscopy has witnessed significant advancements in spatial and temporal resolution, as well as improvements in optical microscope imaging quality. However, these advancements have concurrently raised the demand...

Multimodality Fusion Strategies in Eye Disease Diagnosis.

Journal of imaging informatics in medicine
Multimodality fusion has gained significance in medical applications, particularly in diagnosing challenging diseases like eye diseases, notably diabetic eye diseases that pose risks of vision loss and blindness. Mono-modality eye disease diagnosis p...

OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods.

Scientific data
Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of retinal d...

Accuracy of generative deep learning model for macular anatomy prediction from optical coherence tomography images in macular hole surgery.

Scientific reports
This study aims to propose a generative deep learning model (GDLM) based on a variational autoencoder that predicts macular optical coherence tomography (OCT) images following full-thickness macular hole (FTMH) surgery and evaluate its clinical accur...

Deep-learning automated quantification of longitudinal OCT scans demonstrates reduced RPE loss rate, preservation of intact macular area and predictive value of isolated photoreceptor degeneration in geographic atrophy patients receiving C3 inhibition treatment.

The British journal of ophthalmology
OBJECTIVE: To evaluate the role of automated optical coherence tomography (OCT) segmentation, using a validated deep-learning model, for assessing the effect of C3 inhibition on the area of geographic atrophy (GA); the constituent features of GA on O...

Improved modeling of human vision by incorporating robustness to blur in convolutional neural networks.

Nature communications
Whenever a visual scene is cast onto the retina, much of it will appear degraded due to poor resolution in the periphery; moreover, optical defocus can cause blur in central vision. However, the pervasiveness of blurry or degraded input is typically ...