AIMC Topic: Macular Degeneration
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Prediction of activity in eyes with macular neovascularization due to age-related macular degeneration using deep learning.
Eye (London, England)
Oct 26, 2023
Automatic detection and differential diagnosis of age-related macular degeneration from color fundus photographs using deep learning with hierarchical vision transformer.
Computers in biology and medicine
Oct 25, 2023
Age-related macular degeneration (AMD) is a leading cause of vision loss in the elderly, highlighting the need for early and accurate detection. In this study, we proposed DeepDrAMD, a hierarchical vision transformer-based deep learning model that in...
Few-shot out-of-distribution detection for automated screening in retinal OCT images using deep learning.
Scientific reports
Sep 27, 2023
Deep neural networks have been increasingly proposed for automated screening and diagnosis of retinal diseases from optical coherence tomography (OCT), but often provide high-confidence predictions on out-of-distribution (OOD) cases, compromising the...
Understanding and interpreting CNN's decision in optical coherence tomography-based AMD detection.
European journal of ophthalmology
Sep 6, 2023
INTRODUCTION: Automated assessment of age-related macular degeneration (AMD) using optical coherence tomography (OCT) has gained significant research attention in recent years. Though a list of convolutional neural network (CNN)-based methods has bee...
Deep-learning based automated quantification of critical optical coherence tomography features in neovascular age-related macular degeneration.
Eye (London, England)
Sep 5, 2023
PURPOSE: To validate a deep learning algorithm for automated intraretinal fluid (IRF), subretinal fluid (SRF) and neovascular pigment epithelium detachment (nPED) segmentations in neovascular age-related macular degeneration (nAMD).
Automated Age-Related Macular Degeneration Detector on Optical Coherence Tomography Images Using Slice-Sum Local Binary Patterns and Support Vector Machine.
Sensors (Basel, Switzerland)
Aug 22, 2023
Artificial intelligence has revolutionised smart medicine, resulting in enhanced medical care. This study presents an automated detector chip for age-related macular degeneration (AMD) using a support vector machine (SVM) and three-dimensional (3D) o...
Unraveling the complexity of Optical Coherence Tomography image segmentation using machine and deep learning techniques: A review.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 14, 2023
Optical Coherence Tomography (OCT) is an emerging technology that provides three-dimensional images of the microanatomy of biological tissue in-vivo and at micrometer-scale resolution. OCT imaging has been widely used to diagnose and manage various m...
Cross-camera Performance of Deep Learning Algorithms to Diagnose Common Ophthalmic Diseases: A Comparative Study Highlighting Feasibility to Portable Fundus Camera Use.
Current eye research
May 29, 2023
PURPOSE: To compare the inter-camera performance and consistency of various deep learning (DL) diagnostic algorithms applied to fundus images taken from desktop Topcon and portable Optain cameras.
FundusQ-Net: A regression quality assessment deep learning algorithm for fundus images quality grading.
Computer methods and programs in biomedicine
May 26, 2023
OBJECTIVE: Ophthalmological pathologies such as glaucoma, diabetic retinopathy and age-related macular degeneration are major causes of blindness and vision impairment. There is a need for novel decision support tools that can simplify and speed up t...
Deep learning for detection of age-related macular degeneration: A systematic review and meta-analysis of diagnostic test accuracy studies.
PloS one
Apr 6, 2023
OBJECTIVE: To evaluate the diagnostic accuracy of deep learning algorithms to identify age-related macular degeneration and to explore factors impacting the results for future model training.
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