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Retinal Vessel Segmentation and Disc Detection from Color Fundus Images Using Inception Module and Residual Connection
Relating to diagnosis of ophthalmologic diseases, retinal fundus images provide valuable clinical information. Retinal blood vessel analysis gives...
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A Fusion Based Approach for Blood Vessel Segmentation from Fundus Images by Separating Brighter Optic Disc
Abstract—In ophthalmology, blood vessel segmentation from fundus images plays a significant role in automated retinal disease screening systems....
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Translating Justice: A Cross-Lingual Information Retrieval System for Maltese Case Law Documents
In jurisdictions adhering to the Common Law system, previous court judgements inform future rulings based on the Stare Decisis principle. For...
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Blood vessel segmentation in retinal fundus images for proliferative diabetic retinopathy screening using deep learning
Diabetic retinopathy (DR) is also called diabetic eye disease, which causes damage to the retina due to diabetes mellitus and that leads to blindness...
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Blood vessel segmentation and extraction using H-minima method based on image processing techniques
In this paper, the H-minima transform is used for blood vessel segmentation. The aim of this study is to get the high accuracy of blood vessel...
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Supervised learning-based retinal vascular segmentation by M-UNet full convolutional neural network
The accurate vessel segmentation for retinal image is the most conducive to early diagnosis of various eye-related diseases. Most deep learning...
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Segmentation of Significant Regions in Retinal Images: Perspective of U-Net Network Through a Comparative Approach
The main aim of this article is to compare U-Net models with different methods of medical image segmentation in ophthalmology when searching for the...
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Construction and verification of retinal vessel segmentation algorithm for color fundus image under BP neural network model
To improve the accuracy of retinal vessel segmentation, a retinal vessel segmentation algorithm for color fundus images based on back-propagation...
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GUNet: A GCN-CNN Hybrid Model for Retinal Vessel Segmentation by Learning Graphical Structures
In the retinal vessel segmentation task, maintaining graphical structures of vessels is important for the following analysis steps. However, this...
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HPWO-LS-based deep learning approach with S-ROA-optimized optic cup segmentation for fundus image classification
Recently, automated retinal image processing has been considered a competitive field of research due to the low-accuracy results, complexity, and...
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Optic disc analysis in retinal fundus using L2 norm of contourlet subbands, superimposed edges, and morphological filling
Optic disc (OD) analysis is an important stage in detecting retinal diseases and existing approaches are not suitable for analyzing multiple...
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Deep feature extraction via adaptive collaborative learning for drusen segmentation from fundus images
Drusen are an early sign of non-neovascular age-related macular degeneration which is a major factor of irreversible blindness. Drusen segmentation...
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Retinal Vessel Segmentation Network Based on Patch-GAN
In order to segment the blood vessels from the retina more accurately, a new retinal vessel segmentation network called Patch-GAN is proposed in this...
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Survey on retinal vessel segmentation
The primary causes of vision loss are disorders of the retina, such as diabetic retinopathy (DR). The ability to segment blood vessels in retinal...
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ARDC-UNet retinal vessel segmentation with adaptive residual deformable convolutional based U-Net
To extract maximum features ResAttNet (RAN) network structure is chosen as an alternative to the convolutional layer and it enhances image feature...
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MES-Net: a new network for retinal image segmentation
Glaucoma, diabetic retinopathy, and other eye diseases have seriously threatened people’s visual health. Whether it is clinical diagnosis or...
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Attention to fine-grained information: hierarchical multi-scale network for retinal vessel segmentation
Medical segmentation is a task that pays attention to details. The rapid development of deep learning in image processing technology makes it...
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Deep learning of fundus images and optical coherence tomography images for ocular disease detection – a review
Deep Learning (DL) has proliferated interest in ocular disease detection in recent years, and several DL architectures were proposed. DL...
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Improving Morphology and Recurrent Residual Refinement Network to Classify Hypertension in Retinal Vessel Image
Prolonged or severe hypertension leads to vascular changes, resulting in endothelial damage and necrosis. The hypertension classification based on...
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A novel methodology for vessel extraction from retinal fundus image and detection of neovascularization
Vessel extraction from the retinal fundus images plays a significant role in ophthalmologic disease diagnosis. Proliferative Diabetic Retinopathy...
