AIMC Topic: Retina
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Development and validation of a deep learning system to screen vision-threatening conditions in high myopia using optical coherence tomography images.
The British journal of ophthalmology
Dec 21, 2020
BACKGROUND/AIMS: To apply deep learning technology to develop an artificial intelligence (AI) system that can identify vision-threatening conditions in high myopia patients based on optical coherence tomography (OCT) macular images.
A novel deep learning conditional generative adversarial network for producing angiography images from retinal fundus photographs.
Scientific reports
Dec 9, 2020
Fluorescein angiography (FA) is a procedure used to image the vascular structure of the retina and requires the insertion of an exogenous dye with potential adverse side effects. Currently, there is only one alternative non-invasive system based on O...
DeepRetina: Layer Segmentation of Retina in OCT Images Using Deep Learning.
Translational vision science & technology
Dec 9, 2020
PURPOSE: To automate the segmentation of retinal layers, we propose DeepRetina, a method based on deep neural networks.
How to Extract More Information With Less Burden: Fundus Image Classification and Retinal Disease Localization With Ophthalmologist Intervention.
IEEE journal of biomedical and health informatics
Dec 4, 2020
Image classification using convolutional neural networks (CNNs) outperforms other state-of-the-art methods. Moreover, attention can be visualized as a heatmap to improve the explainability of results of a CNN. We designed a framework that can generat...
End-to-End Deep Learning Model for Predicting Treatment Requirements in Neovascular AMD From Longitudinal Retinal OCT Imaging.
IEEE journal of biomedical and health informatics
Dec 4, 2020
Neovascular age-related macular degeneration (nAMD) is nowadays successfully treated with anti-VEGF substances, but inter-individual treatment requirements are vastly heterogeneous and currently poorly plannable resulting in suboptimal treatment freq...
MS-CAM: Multi-Scale Class Activation Maps for Weakly-Supervised Segmentation of Geographic Atrophy Lesions in SD-OCT Images.
IEEE journal of biomedical and health informatics
Dec 4, 2020
As one of the most critical characteristics in advanced stage of non-exudative Age-related Macular Degeneration (AMD), Geographic Atrophy (GA) is one of the significant causes of sustained visual acuity loss. Automatic localization of retinal regions...
Dehaze of Cataractous Retinal Images Using an Unpaired Generative Adversarial Network.
IEEE journal of biomedical and health informatics
Dec 4, 2020
Cataracts are the leading cause of visual impairment worldwide. Examination of the retina through cataracts using a fundus camera is challenging and error-prone due to degraded image quality. We sought to develop an algorithm to dehaze such images to...
UD-MIL: Uncertainty-Driven Deep Multiple Instance Learning for OCT Image Classification.
IEEE journal of biomedical and health informatics
Dec 4, 2020
Deep learning has achieved remarkable success in the optical coherence tomography (OCT) image classification task with substantial labelled B-scan images available. However, obtaining such fine-grained expert annotations is usually quite difficult an...
Deep learning-based classification and segmentation of retinal cavitations on optical coherence tomography images of macular telangiectasia type 2.
The British journal of ophthalmology
Nov 23, 2020
AIM: To develop a fully automatic algorithm to segment retinal cavitations on optical coherence tomography (OCT) images of macular telangiectasia type 2 (MacTel2).
A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification.
Medical image analysis
Nov 17, 2020
The eye affords a unique opportunity to inspect a rich part of the human microvasculature non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are prime steps for the diagnosis and risk assessment of microvascular ...
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