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 …
DeepFire: A novel dataset and deep transfer learning benchmark for forest fire detection
Forest fires pose a potential threat to the ecological and environmental systems and natural
resources, impacting human lives. However, automated surveillance system for early forest …
resources, impacting human lives. However, automated surveillance system for early forest …
Computer aided diagnosis of diabetic macular edema in retinal fundus and OCT images: A review
KC Pavithra, P Kumar, M Geetha… - Biocybernetics and …, 2023 - Elsevier
Abstract Diabetic Macular Edema (DME) is a potentially blinding consequence of Diabetic
Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is …
Retinopathy (DR) as well as the leading cause of vision loss in diabetics. DME is …
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 …
RetiFluidNet: a self-adaptive and multi-attention deep convolutional network for retinal OCT fluid segmentation
Optical coherence tomography (OCT) helps ophthalmologists assess macular edema,
accumulation of fluids, and lesions at microscopic resolution. Quantification of retinal fluids is …
accumulation of fluids, and lesions at microscopic resolution. Quantification of retinal fluids is …
TSSK-Net: Weakly supervised biomarker localization and segmentation with image-level annotation in retinal OCT images
The localization and segmentation of biomarkers in OCT images are critical steps in retina-
related disease diagnosis. Although fully supervised deep learning models can segment …
related disease diagnosis. Although fully supervised deep learning models can segment …
An improved supervised and attention mechanism-based U-Net algorithm for retinal vessel segmentation
Z Ma, X Li - Computers in Biology and Medicine, 2024 - Elsevier
The segmentation results of retinal blood vessels are crucial for automatically diagnosing
ophthalmic diseases such as diabetic retinopathy, hypertension, cardiovascular and …
ophthalmic diseases such as diabetic retinopathy, hypertension, cardiovascular and …
A deep ensemble learning-based CNN architecture for multiclass retinal fluid segmentation in oct images
Retinal Fluids (fluid collections) develop because of the accumulation of fluid in the retina,
which may be caused by several retinal disorders, and can lead to loss of vision. Optical …
which may be caused by several retinal disorders, and can lead to loss of vision. Optical …
Hybrid machine-learning-based spectrum sensing and allocation with adaptive congestion-aware modeling in CR-assisted IoV networks
Unlicensed cognitive-radio (CR)-assisted Internet of Vehicles (IoV) users can access
licensed providers' radio spectrum and concurrently utilize the dedicated channel for data …
licensed providers' radio spectrum and concurrently utilize the dedicated channel for data …
A vision transformer architecture for the automated segmentation of retinal lesions in spectral domain optical coherence tomography images
D Philippi, K Rothaus, M Castelli - Scientific Reports, 2023 - nature.com
Neovascular age-related macular degeneration (nAMD) is one of the major causes of
irreversible blindness and is characterized by accumulations of different lesions inside the …
irreversible blindness and is characterized by accumulations of different lesions inside the …