[HTML][HTML] Strategies to improve convolutional neural network generalizability and reference standards for glaucoma detection from OCT scans
Purpose: To develop and evaluate methods to improve the generalizability of convolutional
neural networks (CNNs) trained to detect glaucoma from optical coherence tomography …
neural networks (CNNs) trained to detect glaucoma from optical coherence tomography …
Review of visualization approaches in deep learning models of glaucoma
B Gu, S Sidhu, RN Weinreb… - The Asia-Pacific …, 2022 - journals.lww.com
Glaucoma is a major cause of irreversible blindness worldwide. As glaucoma often presents
without symptoms, early detection and intervention are important in delaying progression …
without symptoms, early detection and intervention are important in delaying progression …
Iterative quality control strategies for expert medical image labeling
Data quality is a key concern for artificial intelligence (AI) efforts that rely on crowdsourced
data collection. In the domain of medicine in particular, labeled data must meet high quality …
data collection. In the domain of medicine in particular, labeled data must meet high quality …
Deep learning: applications in retinal and optic nerve diseases
J Charng, K Alam, G Swartz, J Kugelman… - Clinical and …, 2023 - Taylor & Francis
Deep learning (DL) represents a paradigm-shifting, burgeoning field of research with
emerging clinical applications in optometry. Unlike traditional programming, which relies on …
emerging clinical applications in optometry. Unlike traditional programming, which relies on …
Glaucoma Progression Detection and Humphrey Visual Field Prediction Using Discriminative and Generative Vision Transformers
Glaucoma is one of the top causes of blindness worldwide. Assessing its progression is
critical to determine potential visual impairment and to design sound treatment plans …
critical to determine potential visual impairment and to design sound treatment plans …
Comparison between deep-learning-based ultra-wide-field fundus imaging and true-colour confocal scanning for diagnosing glaucoma
In this retrospective, comparative study, we evaluated and compared the performance of two
confocal imaging modalities in detecting glaucoma based on a deep learning (DL) classifier …
confocal imaging modalities in detecting glaucoma based on a deep learning (DL) classifier …
Artificial intelligence for detection of optic disc abnormalities
D Milea, S Singhal, RP Najjar - Current Opinion in Neurology, 2020 - journals.lww.com
Artificial intelligence and in particular newly developed deep-learning systems are playing
an increasingly important role for the detection and classification of acquired neuro …
an increasingly important role for the detection and classification of acquired neuro …
The Definition of Glaucomatous Optic Neuropathy in Artificial Intelligence Research and Clinical Applications
Objective Although artificial intelligence (AI) models may offer innovative and powerful ways
to use the wealth of data generated by diagnostic tools, there are important challenges …
to use the wealth of data generated by diagnostic tools, there are important challenges …
Cross-camera performance of deep learning algorithms to diagnose common ophthalmic diseases: a comparative study highlighting feasibility to portable fundus …
S He, G Bulloch, L Zhang, Y Xie, W Wu, Y He… - Current Eye …, 2023 - Taylor & Francis
Purpose To compare the inter-camera performance and consistency of various deep
learning (DL) diagnostic algorithms applied to fundus images taken from desktop Topcon …
learning (DL) diagnostic algorithms applied to fundus images taken from desktop Topcon …
A study to identify limitations of existing automated systems to detect glaucoma at initial and curable stage
Glaucoma ocular disease is the second topmost reason for irreversible visual impairment
around the world. This malady can be cured and permanent blindness can be prevented by …
around the world. This malady can be cured and permanent blindness can be prevented by …