AIMC Topic: Fundus Oculi

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Diagnostic Quality Assessment of Ocular Fundus Photographs: Efficacy of Structure-Preserving ScatNet Features.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Various ophthalmic procedures critically depend on high-quality images. For instance, efficiency of teleophthalmology, a framework to bring advanced eye care to remote regions, is determined by the capability of assessing diagnostic quality of ocular...
Humans Machine Learning Algorithms Diagnostic Techniques, Ophthalmological Photography Eye Ophthalmology Fundus Oculi Telemedicine
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An Interpretable Ensemble Deep Learning Model for Diabetic Retinopathy Disease Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Diabetic retinopathy (DR) is one kind of eye disease that is caused by overtime diabetes. Lots of patients around the world suffered from DR which may bring about blindness. Early detection of DR is a rigid quest which can remind the DR patients to s...
Algorithms Fundus Oculi Deep Learning Diabetes Mellitus Humans Diabetic Retinopathy
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Conditional Adversarial Transfer for Glaucoma Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Deep learning has achieved great success in image classification task when given sufficient labeled training images. However, in fundus image based glaucoma diagnosis, we often have very limited training data due to expensive cost in data labeling. M...
Humans Glaucoma Deep Learning Fundus Oculi Image Interpretation, Computer-Assisted
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Automated Glaucoma Screening from Retinal Fundus Image Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Glaucoma is the second leading cause of blindness worldwide. This paper proposes an automated glaucoma screening method using retinal fundus images via the ensemble technique to fuse the results of different classification networks and the result of ...
Algorithms Deep Learning Fundus Oculi Humans Glaucoma Diagnostic Techniques, Ophthalmological
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Retinal Vessel Segmentation using Round-wise Features Aggregation on Bracket-shaped Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
With the recent advent of deep learning in medical image processing, retinal blood vessel segmentation topic has been comprehensively handled by numerous research works. However, since the ratio between the number of vessel and background pixels is h...
Image Processing, Computer-Assisted Fundus Oculi Retinal Vessels Neural Networks, Computer Deep Learning
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Deep Learning Predicts OCT Measures of Diabetic Macular Thickening From Color Fundus Photographs.

Investigative ophthalmology & visual science Mar 1, 2019
PURPOSE: To develop deep learning (DL) models for the automatic detection of optical coherence tomography (OCT) measures of diabetic macular thickening (MT) from color fundus photographs (CFPs).
Ranibizumab Photography Intravitreal Injections Diagnostic Techniques, Ophthalmological Macula Lutea Image Interpretation, Computer-Assisted False Positive Reactions Humans Diabetic Retinopathy Neural Networks, Computer Retrospective Studies Female Randomized Controlled Trials as Topic Middle Aged Predictive Value of Tests Sensitivity and Specificity Deep Learning Fundus Oculi Tomography, Optical Coherence Male Angiogenesis Inhibitors Macular Edema Vascular Endothelial Growth Factor A
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Assessment of Deep Generative Models for High-Resolution Synthetic Retinal Image Generation of Age-Related Macular Degeneration.

JAMA ophthalmology Mar 1, 2019
IMPORTANCE: Deep learning (DL) used for discriminative tasks in ophthalmology, such as diagnosing diabetic retinopathy or age-related macular degeneration (AMD), requires large image data sets graded by human experts to train deep convolutional neura...
Macular Degeneration Diagnostic Techniques, Ophthalmological Humans Reproducibility of Results Deep Learning Fundus Oculi
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Laterality Classification of Fundus Images Using Interpretable Deep Neural Network.

Journal of digital imaging Dec 1, 2018
In this paper, we aimed to understand and analyze the outputs of a convolutional neural network model that classifies the laterality of fundus images. Our model not only automatizes the classification process, which results in reducing the labors of ...
Retinal Vessels Reproducibility of Results Fundus Oculi Eye Diseases Humans Algorithms Neural Networks, Computer Databases, Factual
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Automated Segmentation and Quantification of Drusen in Fundus and Optical Coherence Tomography Images for Detection of ARMD.

Journal of digital imaging Aug 1, 2018
Age-related macular degeneration (ARMD) is one of the most common retinal syndromes that occurs in elderly people. Different eye testing techniques such as fundus photography and optical coherence tomography (OCT) are used to clinically examine the A...
Middle Aged Severity of Illness Index Macular Degeneration Aged Humans Decision Support Systems, Clinical Male Support Vector Machine Female Tomography, Optical Coherence Fundus Oculi
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Introducing a Novel Layer in Convolutional Neural Network for Automatic Identification of Diabetic Retinopathy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Convolutional neural networks have been widely used for identifying diabetic retinopathy on color fundus images. For such application, we proposed a novel framework for the convolutional neural network architecture by embedding a preprocessing layer ...
Hemorrhage Image Enhancement Exudates and Transudates Microaneurysm Neural Networks, Computer Humans Algorithms Diabetic Retinopathy Fundus Oculi
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