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Classification of pachychoroid disease on ultrawide-field indocyanine green angiography using auto-machine learning platform.
The British journal of ophthalmology
Jul 3, 2020
AIMS: Automatic identification of pachychoroid maybe used as an adjunctive method to confirm the condition and be of help in treatment for macular diseases. This study investigated the feasibility of classifying pachychoroid disease on ultra-widefiel...
From Local to Global: A Graph Framework for Retinal Artery/Vein Classification.
IEEE transactions on nanobioscience
Jun 23, 2020
Fundus photography has been widely used for inspecting eye disorders by ophthalmologists or computer algorithms. Biomarkers related to retinal vessels plays an essential role to detect early diabetes. To quantify vascular biomarkers or the correspond...
Automated diagnoses of age-related macular degeneration and polypoidal choroidal vasculopathy using bi-modal deep convolutional neural networks.
The British journal of ophthalmology
Jun 4, 2020
AIMS: To investigate the efficacy of a bi-modality deep convolutional neural network (DCNN) framework to categorise age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) from colour fundus images and optical coherence tom...
Deep Learning Automated Detection of Reticular Pseudodrusen from Fundus Autofluorescence Images or Color Fundus Photographs in AREDS2.
Ophthalmology
May 21, 2020
PURPOSE: To develop deep learning models for detecting reticular pseudodrusen (RPD) using fundus autofluorescence (FAF) images or, alternatively, color fundus photographs (CFP) in the context of age-related macular degeneration (AMD).
Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software.
Current eye research
May 15, 2020
: To describe the development and validation of an artificial intelligence-based, deep learning algorithm (DeepDR) for the detection of diabetic retinopathy (DR) in retinal fundus photographs. : Five hundred fundus images, which had detailed labellin...
Ensemble Deep Learning for Diabetic Retinopathy Detection Using Optical Coherence Tomography Angiography.
Translational vision science & technology
Apr 13, 2020
PURPOSE: To evaluate the role of ensemble learning techniques with deep learning in classifying diabetic retinopathy (DR) in optical coherence tomography angiography (OCTA) images and their corresponding co-registered structural images.
Determinants of Cone and Rod Functions in Geographic Atrophy: AI-Based Structure-Function Correlation.
American journal of ophthalmology
Apr 11, 2020
PURPOSE: To investigate the association between retinal microstructure and cone and rod function in geographic atrophy (GA) secondary to age-related macular degeneration (AMD) by using artificial intelligence (AI) algorithms.
Diabetic retinopathy and ultrawide field imaging.
Seminars in ophthalmology
Mar 13, 2020
The introduction of ultrawide field imaging has allowed the visualization of approximately 82% of the total retinal area compared to only 30% using 7-standard field Early Treatment Diabetic Retinopathy (ETDRS) photography. This substantially wider fi...
Exploring the effect of hypertension on retinal microvasculature using deep learning on East Asian population.
PloS one
Mar 5, 2020
Hypertension is the leading risk factor of cardiovascular disease and has profound effects on both the structure and function of the microvasculature. Abnormalities of the retinal vasculature may reflect the degree of microvascular damage due to hype...
A Deep Learning Model for Segmentation of Geographic Atrophy to Study Its Long-Term Natural History.
Ophthalmology
Feb 15, 2020
PURPOSE: To develop and validate a deep learning model for the automatic segmentation of geographic atrophy (GA) using color fundus images (CFIs) and its application to study the growth rate of GA.
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