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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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A Transformer-Assisted Cascade Learning Network for Choroidal Vessel Segmentation
As a highly vascular eye part, the choroid is crucial in various eye disease diagnoses. However, limited research has focused on the inner structure...
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SATTA: Semantic-Aware Test-Time Adaptation for Cross-Domain Medical Image Segmentation
Cross-domain distribution shift is a common problem for medical image analysis because medical images from different devices usually own varied...
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Graph-Constrained Contrastive Regularization for Semi-weakly Volumetric Segmentation
Semantic volume segmentation suffers from the requirement of having voxel-wise annotated ground-truth data, which requires immense effort to obtain....
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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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Unsupervised Domain Adaptation with Contrastive Learning for OCT Segmentation
Accurate segmentation of retinal fluids in 3D Optical Coherence Tomography images is key for diagnosis and personalized treatment of eye diseases....
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Adapting Segment Anything Model (SAM) for Retinal OCT
The Segment Anything Model (SAM) has gained significant attention in the field of image segmentation due to its impressive capabilities and...
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A Feature Pyramid Fusion Network Based on Dynamic Perception Transformer for Retinal OCT Biomarker Image Segmentation
OCT biomarkers are important for assessing the developmental stages of retinal diseases. However, the biomarkers show diverse and irregular features...
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Uncertainty-Guided Pixel-Level Contrastive Learning for Biomarker Segmentation in OCT Images
Optical coherence tomography (OCT) has been widely leveraged to assist doctors in clinical ophthalmic diagnosis, since it can show the hierarchical...
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Unsupervised Domain Adaptation with Self-selected Active Learning for Cross-domain OCT Image Segmentation
Segmentation of optical coherence tomography (OCT) images of retinal tissue has become an important task for the diagnosis and management of eye...
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Choroidal Neovascularization Segmentation Based on 3D CNN with Cross Convolution Module
Choroidal neovascularization (CNV) is a retinal vascular disease that new vessels sprout from the choroid and then grow into retina, which usually...
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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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Noise Transfer for Unsupervised Domain Adaptation of Retinal OCT Images
Optical coherence tomography (OCT) imaging from different camera devices causes challenging domain shifts and can cause a severe drop in accuracy for...
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ReLaX: Retinal Layer Attribution for Guided Explanations of Automated Optical Coherence Tomography Classification
30 million Optical Coherence Tomography (OCT) imaging tests are issued annually to diagnose various retinal diseases, but accurate diagnosis of OCT...
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Ocular disease detection systems based on fundus images: a survey
Ocular diseases are a leading cause of blindness and early detection is crucial for preventing permanent eye damage. Traditionally, instruments such...
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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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Clustering Disease Trajectories in Contrastive Feature Space for Biomarker Proposal in Age-Related Macular Degeneration
Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly. Current grading systems based on imaging biomarkers only...
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A comprehensive review of artificial intelligence models for screening major retinal diseases
This paper provides a systematic survey of artificial intelligence (AI) models that have been proposed over the past decade to screen retinal...
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Beyond Retinal Layers: A Large Blob Detection for Subretinal Fluid Segmentation in SD-OCT Images
Purpose: To automatically segment neurosensory retinal detachment (NRD)-associated subretinal fluid in spectral domain optical coherence tomography...
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Comprehensive fully-automatic multi-depth grading of the clinical types of macular neovascularization in OCTA images
Optical Coherence Tomography Angiography or OCTA represents one of the main means of diagnosis of Age-related Macular Degeneration (AMD), the leading...
