AIMC Topic: Retina

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An attentional mechanism model for segmenting multiple lesion regions in the diabetic retina.

Scientific reports
Diabetic retinopathy (DR), a leading cause of blindness in diabetic patients, necessitates the precise segmentation of lesions for the effective grading of lesions. DR multi-lesion segmentation faces the main concerns as follows. On the one hand, ret...

Validation of neuron activation patterns for artificial intelligence models in oculomics.

Scientific reports
Recent advancements in artificial intelligence (AI) have prompted researchers to expand into the field of oculomics; the association between the retina and systemic health. Unlike conventional AI models trained on well-recognized retinal features, th...

Artificial intelligence for retinal diseases.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To discuss the worldwide applications and potential impact of artificial intelligence (AI) for the diagnosis, management and analysis of treatment outcomes of common retinal diseases.

Wavelet-based selection-and-recalibration network for Parkinson's disease screening in OCT images.

Computer methods and programs in biomedicine
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
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
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
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
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
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...