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Analysis of Light and Dark Pixel Density Areas on SD-OCT in Diabetes—Is It a Marker of Neuronal Degeneration?
The aim of the study was to analyze the spectral-domain optical coherence tomography (SD-OCT) images in terms of light and dark pixels; thus,...
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Ocular diseases classification using a lightweight CNN and class weight balancing on OCT images
Optical coherence tomography (OCT) is a non-invasive technique to capture cross-sectional volumes of the human retina. OCT images are used for the...
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SD-LayerNet: Semi-supervised Retinal Layer Segmentation in OCT Using Disentangled Representation with Anatomical Priors
Optical coherence tomography (OCT) is a non-invasive 3D modality widely used in ophthalmology for imaging the retina. Achieving automated,...
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Deep learning-enabled automatic screening of SLE diseases and LR using OCT images
Optical coherence tomography (OCT) is a noninvasive imaging technique that enables the visualization of tissue microstructure in vivo. Recent studies...
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Enhancing OCT patch-based segmentation with improved GAN data augmentation and semi-supervised learning
For optimum performance, deep learning methods, such as those applied for retinal and choroidal layer segmentation in optical coherence tomography...
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Automated end-to-end Architecture for Retinal Layers and Fluids Segmentation on OCT B-scans
Age-related macular degeneration (AMD) is a degenerative retina condition that causes notable visual impairment in the central area of the visual...
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An automated hybrid decoupled convolutional network for laceration segmentation and grading of retinal diseases using optical coherence tomography (OCT) images
Diabetic retinopathy (DR) is a complication of diabetes that damages the retina and can cause blindness if untreated due to high blood sugar levels....
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Data-Dependence Dual Path Network for Choroidal Neovascularization Segmentation in SD-OCT Images
Choroidal neovascularization (CNV) is a typical clinical manifestation of age-related macular degeneration (AMD) and an important factor leading to...
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Unsupervised real-time evaluation of optical coherence tomography (OCT) images of solid oral dosage forms
Automatic segmentation of images, which is now feasible through an increase in available computing power, has become an important challenge in many...
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Detection of retinal disorders from OCT images using generative adversarial networks
Retinal image analysis has opened up a new window for prompt diagnosis and detection of various retinal disorders. Optical Coherence Tomography (OCT)...
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3D Deep Learning-based Boundary Regression of an Age-related Retinal Biomarker in High Resolution OCT
Vision is essential for quality of life, but is threatened by visionimpairing diseases like age-related macular degeneration (AMD). A recently...
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A Fast Method for Retinal Disease Classification from OCT Images Using Depthwise Separable Convolution
Retinal diseases are the commonest reason for losing eye sight at an early age. The retina is the most important part of forming visual images, which...
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EdgeAL: An Edge Estimation Based Active Learning Approach for OCT Segmentation
Active learning algorithms have become increasingly popular for training models with limited data. However, selecting data for annotation remains a...
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Facing Annotation Redundancy: OCT Layer Segmentation with only 10 Annotated Pixels per Layer
The retinal layer segmentation from OCT images is a fundamental and important task in the diagnosis and monitoring of eye-related diseases. The quest...
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Data augmentation for patch-based OCT chorio-retinal segmentation using generative adversarial networks
Many clinical and research tasks rely critically upon the segmentation of tissue layers in optical coherence tomography (OCT) images of the posterior...
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Weakly Supervised Retinal Detachment Segmentation Using Deep Feature Propagation Learning in SD-OCT Images
Most automated segmentation approaches for quantitative assessment of sub-retinal fluid regions rely heavily on retinal anatomy knowledge (e.g. layer...
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Gaussian Distribution Prior Based Multi-view Self-supervised Learning for Serous Retinal Detachment Segmentation
Assessment of serous retinal detachment (SRD) plays an important role in the diagnosis of central serous chorioretinopathy (CSC). In this paper, we...
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Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT
In medical imaging, there are clinically relevant segmentation tasks where the output mask is a projection to a subset of input image dimensions. In...
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Automated retinal disease classification using hybrid transformer model (SViT) using optical coherence tomography images
Optical coherence tomography (OCT) is a widely used imaging technique in ophthalmology for diagnosis and treatment. Recent advances in deep neural...
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Automatic retinal layer segmentation in SD-OCT images with CSC guided by spatial characteristics
Segmentation of retinal layers with central serious chorioretinopathy (CSC) in Spectral Domain Optical Coherence Tomography (SD-OCT) images is...
