AIMC Topic: Fundus Oculi
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Optical Disc Segmentation from Retinal Fundus Images Using Deep Learning.
Studies in health technology and informatics
Jun 29, 2023
The optical disc in the human retina can reveal important information about a person's health and well-being. We propose a deep learning-based approach to automatically identify the region in human retinal images that corresponds to the optical disc....
A Deep Learning-Based Approach Towards Simultaneous Localization of Optic Disc and Fovea from Retinal Fundus Images.
Studies in health technology and informatics
Jun 29, 2023
In this work, we propose a multi-task learning-based approach towards the localization of optic disc and fovea from human retinal fundus images using a deep learning-based approach. Formulating the task as an image-based regression problem, we propos...
Deep learning-based detection of diabetic macular edema using optical coherence tomography and fundus images: A meta-analysis.
Indian journal of ophthalmology
May 1, 2023
Diabetic macular edema (DME) is an important cause of visual impairment in the working-age group. Deep learning methods have been developed to detect DME from two-dimensional retinal images and also from optical coherence tomography (OCT) images. The...
Estimation of Visual Function Using Deep Learning From Ultra-Widefield Fundus Images of Eyes With Retinitis Pigmentosa.
JAMA ophthalmology
Apr 1, 2023
IMPORTANCE: There is no widespread effective treatment to halt the progression of retinitis pigmentosa. Consequently, adequate assessment and estimation of residual visual function are important clinically.
Neurologic Dysfunction Assessment in Parkinson Disease Based on Fundus Photographs Using Deep Learning.
JAMA ophthalmology
Mar 1, 2023
IMPORTANCE: Until now, other than complex neurologic tests, there have been no readily accessible and reliable indicators of neurologic dysfunction among patients with Parkinson disease (PD). This study was conducted to determine the role of fundus p...
Solving data quality issues of fundus images in real-world settings by ophthalmic AI.
Cell reports. Medicine
Feb 21, 2023
Liu et al. develop a deep-learning-based flow cytometry-like image quality classifier, DeepFundus, for the automated, high-throughput, and multidimensional classification of fundus image quality. DeepFundus significantly improves the real-world perfo...
Automatic Multilabel Classification of Multiple Fundus Diseases Based on Convolutional Neural Network With Squeeze-and-Excitation Attention.
Translational vision science & technology
Jan 3, 2023
PURPOSE: Automatic multilabel classification of multiple fundus diseases is of importance for ophthalmologists. This study aims to design an effective multilabel classification model that can automatically classify multiple fundus diseases based on c...
Deep Learning Model for Static Ocular Torsion Detection Using Synthetically Generated Fundus Images.
Translational vision science & technology
Jan 3, 2023
PURPOSE: The objective of the study is to develop deep learning models using synthetic fundus images to assess the direction (intorsion versus extorsion) and amount (physiologic versus pathologic) of static ocular torsion. Static ocular torsion asses...
[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs].
Zhonghua xin xue guan bing za zhi
Dec 24, 2022
To develop and validate a deep learning model based on fundus photos for the identification of coronary heart disease (CHD) and associated risk factors. Subjects aged>18 years with complete clinical examination data from 149 hospitals and medical e...
Application of Deep Learning for Automated Detection of Polypoidal Choroidal Vasculopathy in Spectral Domain Optical Coherence Tomography.
Translational vision science & technology
Oct 3, 2022
OBJECTIVE: To develop an automated polypoidal choroidal vasculopathy (PCV) screening model to distinguish PCV from wet age-related macular degeneration (wet AMD).
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