AIMC Topic: Retina
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Wavelet-based selection-and-recalibration network for Parkinson's disease screening in OCT images.
Computer methods and programs in biomedicine
Aug 12, 2024
BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is one of the most prevalent neurodegenerative brain diseases worldwide. Therefore, accurate PD screening is crucial for early clinical intervention and treatment. Recent clinical research indicates ...
Metadata-enhanced contrastive learning from retinal optical coherence tomography images.
Medical image analysis
Aug 10, 2024
Deep learning has potential to automate screening, monitoring and grading of disease in medical images. Pretraining with contrastive learning enables models to extract robust and generalisable features from natural image datasets, facilitating label-...
Physics-informed deep generative learning for quantitative assessment of the retina.
Nature communications
Aug 10, 2024
Disruption of retinal vasculature is linked to various diseases, including diabetic retinopathy and macular degeneration, leading to vision loss. We present here a novel algorithmic approach that generates highly realistic digital models of human ret...
Progressive Feature Fusion Attention Dense Network for Speckle Noise Removal in OCT Images.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 9, 2024
Although deep learning for Big Data analytics has achieved promising results in the field of optical coherence tomography (OCT) image denoising, the low recognition rate caused by complex noise distribution and a large number of redundant features is...
Diabetic retinopathy screening with confocal fundus camera and artificial intelligence - assisted grading.
European journal of ophthalmology
Aug 7, 2024
PURPOSE: Screening for diabetic retinopathy (DR) by ophthalmologists is costly and labour-intensive. Artificial Intelligence (AI) for automated DR detection could be a clinically and economically alternative. We assessed the performance of a confocal...
Neural activity shaping in visual prostheses with deep learning.
Journal of neural engineering
Jul 25, 2024
The visual perception provided by retinal prostheses is limited by the overlapping current spread of adjacent electrodes. This reduces the spatial resolution attainable with unipolar stimulation. Conversely, simultaneous multipolar stimulation guided...
A deep learning framework for the early detection of multi-retinal diseases.
PloS one
Jul 25, 2024
Retinal images play a pivotal contribution to the diagnosis of various ocular conditions by ophthalmologists. Extensive research was conducted to enable early detection and timely treatment using deep learning algorithms for retinal fundus images. Qu...
Adaptative machine vision with microsecond-level accurate perception beyond human retina.
Nature communications
Jul 24, 2024
Visual adaptive devices have potential to simplify circuits and algorithms in machine vision systems to adapt and perceive images with varying brightness levels, which is however limited by sluggish adaptation process. Here, the avalanche tuning as f...
A deep learning approach to hard exudates detection and disorganization of retinal inner layers identification on OCT images.
Scientific reports
Jul 19, 2024
The purpose of the study was to detect Hard Exudates (HE) and classify Disorganization of Retinal Inner Layers (DRIL) implementing a Deep Learning (DL) system on optical coherence tomography (OCT) images of eyes with diabetic macular edema (DME). We ...
Biophysical neural adaptation mechanisms enable artificial neural networks to capture dynamic retinal computation.
Nature communications
Jul 16, 2024
Adaptation is a universal aspect of neural systems that changes circuit computations to match prevailing inputs. These changes facilitate efficient encoding of sensory inputs while avoiding saturation. Conventional artificial neural networks (ANNs) h...
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