AIMC Topic: Fundus Oculi

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A deep learning approach for detection of shallow anterior chamber depth based on the hidden features of fundus photographs.

Computer methods and programs in biomedicine Mar 6, 2022
BACKGROUND AND OBJECTIVES: Patients with angle-closure glaucoma (ACG) are asymptomatic until they experience a painful attack. Shallow anterior chamber depth (ACD) is considered a significant risk factor for ACG. We propose a deep learning approach t...
Anterior Chamber Optic Disk Diagnostic Techniques, Ophthalmological Retrospective Studies Deep Learning ROC Curve Fundus Oculi Humans
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Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation.

IEEE transactions on medical imaging Mar 2, 2022
Segmentation is a fundamental task in biomedical image analysis. Unlike the existing region-based dense pixel classification methods or boundary-based polygon regression methods, we build a novel graph neural network (GNN) based deep learning framewo...
Neural Networks, Computer Optic Disk Semantics Image Processing, Computer-Assisted Fundus Oculi
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Curv-Net: Curvilinear structure segmentation network based on selective kernel and multi-Bi-ConvLSTM.

Medical physics Feb 25, 2022
PURPOSE: Accurately segmenting curvilinear structures, for example, retinal blood vessels or nerve fibers, in the medical image is essential to the clinical diagnosis of many diseases. Recently, deep learning has become a popular technology to deal w...
Retinal Vessels Neural Networks, Computer Reproducibility of Results Image Processing, Computer-Assisted Fundus Oculi
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Untangling Computer-Aided Diagnostic System for Screening Diabetic Retinopathy Based on Deep Learning Techniques.

Sensors (Basel, Switzerland) Feb 24, 2022
Diabetic Retinopathy (DR) is a predominant cause of visual impairment and loss. Approximately 285 million worldwide population is affected with diabetes, and one-third of these patients have symptoms of DR. Specifically, it tends to affect the patien...
Fundus Oculi Deep Learning Humans Diabetes Mellitus Diabetic Retinopathy Neural Networks, Computer Computers
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Multi-task deep learning-based survival analysis on the prognosis of late AMD using the longitudinal data in AREDS.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 21, 2022
Age-related macular degeneration (AMD) is the leading cause of vision loss. Some patients experience vision loss over a delayed timeframe, others at a rapid pace. Physicians analyze time-of-visit fundus photographs to predict patient risk of developi...
Prognosis Humans Deep Learning Disease Progression Fundus Oculi Macular Degeneration Survival Analysis
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Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model.

Journal of healthcare engineering Feb 16, 2022
Glaucoma is the second most common cause for blindness around the world and the third most common in Europe and the USA. Around 78 million people are presently living with glaucoma (2020). It is expected that 111.8 million people will have glaucoma b...
Glaucoma Deep Learning Fundus Oculi Humans Optic Disk Neural Networks, Computer
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Detection of microscopic glaucoma through fundus images using deep transfer learning approach.

Microscopy research and technique Feb 15, 2022
Glaucoma disease in humans can lead to blindness if it progresses to the point where it affects the oculus' optic nerve head. It is not easily detected since there are no symptoms, but it can be detected using tonometry, ophthalmoscopy, and perimeter...
Glaucoma Artificial Intelligence Humans Fundus Oculi Machine Learning Deep Learning
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Deep learning model using retinal vascular images for classifying schizophrenia.

Schizophrenia research Feb 14, 2022
Contemporary psychiatric diagnosis still relies on the subjective symptom report of the patient during a clinical interview by a psychiatrist. Given the significant variability in personal reporting and differences in the skill set of psychiatrists, ...
Schizophrenia Retinal Vessels Fundus Oculi Retina Humans Algorithms Deep Learning
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Deep learning-based classification of retinal vascular diseases using ultra-widefield colour fundus photographs.

BMJ open ophthalmology Feb 4, 2022
OBJECTIVE: To assess the ability of a deep learning model to distinguish between diabetic retinopathy (DR), sickle cell retinopathy (SCR), retinal vein occlusions (RVOs) and healthy eyes using ultra-widefield colour fundus photography (UWF-CFP).
Retinal Diseases Humans Photography Diabetic Retinopathy Color Retrospective Studies Fundus Oculi Deep Learning
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Genetic U-Net: Automatically Designed Deep Networks for Retinal Vessel Segmentation Using a Genetic Algorithm.

IEEE transactions on medical imaging Feb 2, 2022
Recently, many methods based on hand-designed convolutional neural networks (CNNs) have achieved promising results in automatic retinal vessel segmentation. However, these CNNs remain constrained in capturing retinal vessels in complex fundus images....
Neural Networks, Computer Retinal Vessels Image Processing, Computer-Assisted Fundus Oculi
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