AIMC Topic: Fundus Oculi

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Performance of automated machine learning in detecting fundus diseases based on ophthalmologic B-scan ultrasound images.

BMJ open ophthalmology Dec 11, 2024
AIM: To evaluate the efficacy of automated machine learning (AutoML) models in detecting fundus diseases using ocular B-scan ultrasound images.
Humans Retinal Diseases Male Middle Aged Ultrasonography Fundus Oculi Machine Learning Female Adult
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Prediction of Visual Acuity After Cataract Surgery by Deep Learning Methods Using Clinical Information and Color Fundus Photography.

Current eye research Dec 9, 2024
PURPOSE: To examine the performance of deep-learning models that predicts the visual acuity after cataract surgery using preoperative clinical information and color fundus photography (CFP).
Cataract Extraction Photography Cataract Fundus Oculi Humans Female Postoperative Period Retrospective Studies Aged Middle Aged Aged, 80 and over Deep Learning Male Visual Acuity
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An innovative methodology for segmenting vessel like structures using artificial intelligence and image processing.

Scientific reports Dec 5, 2024
Innovation is currently driving enhanced performance and productivity across various fields through process automation. However, identifying intricate details in images can often pose challenges due to morphological variations or specific conditions....
Algorithms Image Processing, Computer-Assisted Fundus Oculi Citrus Humans Neural Networks, Computer Artificial Intelligence
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Diabetic retinopathy detection via deep learning based dual features integrated classification model.

Technology and health care : official journal of the European Society for Engineering and Medicine Dec 1, 2024
BackgroundThe primary recognition of diabetic retinopathy (DR) is a pivotal requirement to prevent blindness and vision impairment. This deadly condition is identified by highly qualified professionals by examining colored retinal images.ObjectiveThe...
Support Vector Machine Fundus Oculi Image Interpretation, Computer-Assisted Humans Diabetic Retinopathy Algorithms Deep Learning
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CC-TransXNet: a hybrid CNN-transformer network for automatic segmentation of optic cup and optic disk from fundus images.

Medical & biological engineering & computing Nov 27, 2024
Accurate segmentation of the optic disk (OD) and optic cup (OC) regions of the optic nerve head is a critical step in glaucoma diagnosis. Existing architectures based on convolutional neural networks (CNNs) still suffer from insufficient global infor...
Algorithms Humans Image Processing, Computer-Assisted Neural Networks, Computer Fundus Oculi Glaucoma Optic Disk
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Computer-aided diagnosis of early-stage Retinopathy of Prematurity in neonatal fundus images using artificial intelligence.

Biomedical physics & engineering express Nov 21, 2024
Retinopathy of Prematurity (ROP) is a retinal disorder affecting preterm babies, which can lead to permanent blindness without treatment. Early-stage ROP diagnosis is vital in providing optimal therapy for the neonates. The proposed study predicts ea...
Principal Component Analysis Humans Neural Networks, Computer Fundus Oculi Machine Learning Artificial Intelligence Retina Retinopathy of Prematurity Algorithms ROC Curve Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Infant, Newborn Support Vector Machine Diagnosis, Computer-Assisted
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A Novel Management Challenge in Age-Related Macular Degeneration: Artificial Intelligence and Expert Prediction of Geographic Atrophy.

Ophthalmology. Retina Nov 9, 2024
PURPOSE: The progression of geographic atrophy (GA) secondary to age-related macular degeneration is highly variable among individuals. Prediction of the progression is critical to identify patients who will benefit most from the first treatments cur...
Algorithms Tomography, Optical Coherence Prospective Studies Fundus Oculi Female Macular Degeneration Aged Disease Progression Disease Management Humans Deep Learning Aged, 80 and over Fluorescein Angiography Artificial Intelligence Male Follow-Up Studies Geographic Atrophy Middle Aged Visual Acuity
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Machine learning model for age-related macular degeneration based on heavy metals: The National Health and Nutrition Examination Survey 2005 to 2008.

Scientific reports Nov 6, 2024
Age-related macular degeneration (AMD) is the leading cause of blindness in older people in developed countries. It has been suggested that heavy metal exposure may be associated with the development of AMD, but most studies have focused on the effec...
Humans Metals, Heavy Male Macular Degeneration Aged Cadmium Middle Aged Machine Learning Risk Assessment Aged, 80 and over Age Factors Early Diagnosis Female Nutrition Surveys Adult Predictive Value of Tests Risk Factors Cross-Sectional Studies Environmental Exposure Fundus Oculi
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A generalised computer vision model for improved glaucoma screening using fundus images.

Eye (London, England) Nov 5, 2024
IMPORTANCE: Worldwide, glaucoma is a leading cause of irreversible blindness. Timely detection is paramount yet challenging, particularly in resource-limited settings. A novel, computer vision-based model for glaucoma screening using fundus images co...
Databases, Factual Reproducibility of Results Sensitivity and Specificity Deep Learning ROC Curve Fundus Oculi Humans Glaucoma Algorithms
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Multi-modal representation learning in retinal imaging using self-supervised learning for enhanced clinical predictions.

Scientific reports Nov 5, 2024
Self-supervised learning has become the cornerstone of building generalizable and transferable artificial intelligence systems in medical imaging. In particular, contrastive representation learning techniques trained on large multi-modal datasets hav...
Tomography, Optical Coherence Fundus Oculi Retina Supervised Machine Learning Artificial Intelligence Image Processing, Computer-Assisted Multimodal Imaging Humans
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