AIMC Topic: Retina
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Towards Stroke Biomarkers on Fundus Retinal Imaging: A Comparison Between Vasculature Embeddings and General Purpose 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
Nov 1, 2021
Fundus Retinal imaging is an easy-to-acquire modality typically used for monitoring eye health. Current evidence indicates that the retina, and its vasculature in particular, is associated with other disease processes making it an ideal candidate for...
Generative Image Inpainting for Retinal Images using Generative Adversarial Networks.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
The diagnosis and treatment of eye diseases is heavily reliant on the availability of retinal imagining equipment. To increase accessibility, lower-cost ophthalmoscopes, such as the Arclight, have been developed. However, a common drawback of these d...
Predicting 10-2 Visual Field From Optical Coherence Tomography in Glaucoma Using Deep Learning Corrected With 24-2/30-2 Visual Field.
Translational vision science & technology
Nov 1, 2021
PURPOSE: To investigate whether a correction based on a Humphrey field analyzer (HFA) 24-2/30-2 visual field (VF) can improve the prediction performance of a deep learning model to predict the HFA 10-2 VF test from macular optical coherence tomograph...
[Retinal Imaging as Potential Biomarkers for Dementia].
Brain and nerve = Shinkei kenkyu no shinpo
Nov 1, 2021
Alzheimer's disease (AD) is a leading cause of dementia, and the current diagnostic methods of AD, such as positron emission tomography imaging, have a high cost and poor accessibility. Amyloidβ accumulates in the brain long before the symptomatic on...
Multi-Disease Detection in Retinal Imaging Based on Ensembling Heterogeneous Deep Learning Models.
Studies in health technology and informatics
Sep 21, 2021
Preventable or undiagnosed visual impairment and blindness affect billion of people worldwide. Automated multi-disease detection models offer great potential to address this problem via clinical decision support in diagnosis. In this work, we propose...
Automated deep learning in ophthalmology: AI that can build AI.
Current opinion in ophthalmology
Sep 1, 2021
PURPOSE OF REVIEW: The purpose of this review is to describe the current status of automated deep learning in healthcare and to explore and detail the development of these models using commercially available platforms. We highlight key studies demons...
Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study.
The Lancet. Digital health
Aug 1, 2021
BACKGROUND: Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains unsatisfactory. Our study aimed to train a clinically...
Multicolor image classification using the multimodal information bottleneck network (MMIB-Net) for detecting diabetic retinopathy.
Optics express
Jul 5, 2021
Multicolor (MC) imaging is an imaging modality that records confocal scanning laser ophthalmoscope (cSLO) fundus images, which can be used for the diabetic retinopathy (DR) detection. By utilizing this imaging technique, multiple modal images can be ...
Deep Learning-Based Retinal Nerve Fiber Layer Thickness Measurement of Murine Eyes.
Translational vision science & technology
Jul 1, 2021
PURPOSE: To design a robust and automated estimation method for measuring the retinal nerve fiber layer (RNFL) thickness using spectral domain optical coherence tomography (SD-OCT).
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