Deep learning in retinal optical coherence tomography (OCT): A comprehensive survey
Retinal optical coherence tomography (OCT) images provide fundamental information
regarding the health of the posterior eye (eg, the retina and choroid). Thus, the development …
regarding the health of the posterior eye (eg, the retina and choroid). Thus, the development …
Multi-scale convolutional neural network for automated AMD classification using retinal OCT images
Background and objective Age-related macular degeneration (AMD) is the most common
cause of blindness in developed countries, especially in people over 60 years of age. The …
cause of blindness in developed countries, especially in people over 60 years of age. The …
Deep learning based joint segmentation and characterization of multi-class retinal fluid lesions on OCT scans for clinical use in anti-VEGF therapy
Background In anti-vascular endothelial growth factor (anti-VEGF) therapy, an accurate
estimation of multi-class retinal fluid (MRF) is required for the activity prescription and …
estimation of multi-class retinal fluid (MRF) is required for the activity prescription and …
Intra-and inter-slice contrastive learning for point supervised oct fluid segmentation
OCT fluid segmentation is a crucial task for diagnosis and therapy in ophthalmology. The
current convolutional neural networks (CNNs) supervised by pixel-wise annotated masks …
current convolutional neural networks (CNNs) supervised by pixel-wise annotated masks …
Multi-scale pathological fluid segmentation in OCT with a novel curvature loss in convolutional neural network
G Xing, L Chen, H Wang, J Zhang… - … on Medical Imaging, 2022 - ieeexplore.ieee.org
The segmentation of pathological fluid lesions in optical coherence tomography (OCT),
including intraretinal fluid, subretinal fluid, and pigment epithelial detachment, is of great …
including intraretinal fluid, subretinal fluid, and pigment epithelial detachment, is of great …
Joint segmentation and quantification of chorioretinal biomarkers in optical coherence tomography scans: A deep learning approach
In ophthalmology, chorioretinal biomarkers (CRBMs) play a significant role in detecting,
quantifying, and ameliorating the treatment of chronic eye conditions. Optical coherence …
quantifying, and ameliorating the treatment of chronic eye conditions. Optical coherence …
Automatic segmentation of retinal layers in multiple neurodegenerative disorder scenarios
M Gende, V Mallen, J de Moura… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Retinal Optical Coherence Tomography (OCT) allows the non-invasive direct observation of
the central nervous system, enabling the measurement and extraction of biomarkers from …
the central nervous system, enabling the measurement and extraction of biomarkers from …
An incremental learning approach to automatically recognize pulmonary diseases from the multi-vendor chest radiographs
The human respiratory network is a vital system that provides oxygen supply and
nourishment to the whole body. Pulmonary diseases can cause severe respiratory …
nourishment to the whole body. Pulmonary diseases can cause severe respiratory …
A foundation language-image model of the retina (flair): Encoding expert knowledge in text supervision
Foundation vision-language models are currently transforming computer vision, and are on
the rise in medical imaging fueled by their very promising generalization capabilities …
the rise in medical imaging fueled by their very promising generalization capabilities …
Clinically verified hybrid deep learning system for retinal ganglion cells aware grading of glaucomatous progression
Objective: Glaucoma is the second leading cause of blindness worldwide. Glaucomatous
progression can be easily monitored by analyzing the degeneration of retinal ganglion cells …
progression can be easily monitored by analyzing the degeneration of retinal ganglion cells …