AIMC Topic: Fundus Oculi

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DAU-Net: a novel U-Net with dual attention for retinal vessel segmentation.

Biomedical physics & engineering express Jan 22, 2025
In fundus images, precisely segmenting retinal blood vessels is important for diagnosing eye-related conditions, such as diabetic retinopathy and hypertensive retinopathy or other eye-related disorders. In this work, we propose an enhanced U-shaped n...
Image Interpretation, Computer-Assisted Retinal Vessels Humans Diabetic Retinopathy Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Fundus Oculi
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Deep learning generalization for diabetic retinopathy staging from fundus images.

Physiological measurement Jan 22, 2025
. Diabetic retinopathy (DR) is a serious diabetes complication that can lead to vision loss, making timely identification crucial. Existing data-driven algorithms for DR staging from digital fundus images (DFIs) often struggle with generalization due...
Deep Learning Image Processing, Computer-Assisted Fundus Oculi Humans Diabetic Retinopathy
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ATEDU-NET: An Attention-Embedded Deep Unet for multi-disease diagnosis in chest X-ray images, breast ultrasound, and retina fundus.

Computers in biology and medicine Jan 21, 2025
In image segmentation for medical image analysis, effective upsampling is crucial for recovering spatial information lost during downsampling. This challenge becomes more pronounced when dealing with diverse medical image modalities, which can signif...
Humans Ultrasonography, Mammary Radiography, Thoracic Fundus Oculi Retina Female Deep Learning Image Processing, Computer-Assisted
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Predicting branch retinal vein occlusion development using multimodal deep learning and pre-onset fundus hemisection images.

Scientific reports Jan 21, 2025
Branch retinal vein occlusion (BRVO) is a leading cause of visual impairment in working-age individuals, though predicting its occurrence from retinal vascular features alone remains challenging. We developed a deep learning model to predict BRVO bas...
Retinal Vein Occlusion Male Middle Aged Deep Learning ROC Curve Fundus Oculi Retinal Vessels Retrospective Studies Female Adult Humans
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Systematic application of saliency maps to explain the decisions of convolutional neural networks for glaucoma diagnosis based on disc and cup geometry.

Biomedical physics & engineering express Jan 21, 2025
This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simplified eye fundus images that contain only disc and cup outlines. These simplified images, a methodo...
Glaucoma Algorithms Convolutional Neural Networks Humans Neural Networks, Computer Optic Disk Image Processing, Computer-Assisted Fundus Oculi Image Interpretation, Computer-Assisted
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Adversarial Exposure Attack on Diabetic Retinopathy Imagery Grading.

IEEE journal of biomedical and health informatics Jan 7, 2025
Diabetic Retinopathy (DR) is a leading cause of vision loss around the world. To help diagnose it, numerous cutting-edge works have built powerful deep neural networks (DNNs) to automatically grade DR via retinal fundus images (RFIs). However, RFIs a...
Deep Learning Fundus Oculi Retina Image Interpretation, Computer-Assisted Humans Diabetic Retinopathy Neural Networks, Computer
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Estimating Visual Acuity With Spectacle Correction From Fundus Photos Using Artificial Intelligence.

JAMA network open Jan 2, 2025
IMPORTANCE: Determining spectacle-corrected visual acuity (VA) is essential when managing many ophthalmic diseases. If artificial intelligence (AI) evaluations of macular images estimated this VA from a fundus image, AI might provide spectacle-correc...
Humans Diabetic Retinopathy Artificial Intelligence Eyeglasses Middle Aged Visual Acuity Tomography, Optical Coherence Fundus Oculi Macular Edema Aged Photography Cross-Sectional Studies Algorithms Male Retrospective Studies Female
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Standardized evaluation of diabetic retinopathy using artificial intelligence and its association with metabolic dysfunction-associated steatotic liver disease in Japan: A cross-sectional study.

PloS one Dec 17, 2024
Metabolic dysfunction-associated steatotic liver disease (MASLD) is common in patients with obesity and diabetes and can lead to serious complications. This study aimed to evaluate fundus photographs using artificial intelligence to explore the relat...
Japan Sensitivity and Specificity Image Interpretation, Computer-Assisted Protective Factors Cross-Sectional Studies Photography Glycated Hemoglobin Software Male Cholinesterases Fundus Oculi Middle Aged Female Non-alcoholic Fatty Liver Disease Severity of Illness Index Humans Risk Factors Liver Cirrhosis Diabetic Retinopathy Artificial Intelligence
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Attention and dilated convolutions inclusive deep-CNN with multiplexed texture features to diagnose Pathological and High Myopia.

Computers in biology and medicine Dec 13, 2024
In today's era, precise and timely diagnosis of ocular diseases are crucial as these disorders jeopardize millions of visions. Early detection and proactive management can minimize vision threatening complications from these disorders. High Myopia(HM...
Male Myopia Deep Learning Fundus Oculi Myopia, Degenerative Humans Neural Networks, Computer Female
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Glaucoma detection: Binocular approach and clinical data in machine learning.

Artificial intelligence in medicine Dec 12, 2024
In this work, we present a multi-modal machine learning method to automate early glaucoma diagnosis. The proposed methodology introduces two novel aspects for automated diagnosis not previously explored in the literature: simultaneous use of ocular f...
Decision Trees Fundus Oculi Image Interpretation, Computer-Assisted Neural Networks, Computer Glaucoma Machine Learning Humans
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