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Retinal Image Segmentation Through Valley Emphasis Thresholding of the Gabor Filter Response
The quest for automated diagnosis of diabetic retinopathy continues due to increasing prevalence coupled with scarcity of skilled medical experts,...
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Challenges for ocular disease identification in the era of artificial intelligence
Retinal image analysis is an integral and fundamental step towards the identification and classification of ocular diseases like glaucoma, diabetic...
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An automatic AVR biomarker assessment system in retinal imaging
Retinal Imaging, a non-invasive way to scan the back of the eye, provides a mean to extract different possible biomarkers, such as Artery and Vein...
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DR-VNet: Retinal Vessel Segmentation via Dense Residual UNet
Accurate retinal vessel segmentation is an important task for many computer-aided diagnosis systems. Yet, it is still a challenging problem due to...
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Cascaded Attention Guided Network for Retinal Vessel Segmentation
Segmentation of retinal vessels is of great importance in the diagnosis of eye-related diseases. Many learning-based methods have been proposed for...
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A Semantically Flexible Feature Fusion Network for Retinal Vessel Segmentation
The automatic detection of retinal blood vessels by computer aided techniques plays an important role in the diagnosis of diabetic retinopathy,...
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A novel deep transfer learning based computerized diagnostic Systems for Multi-class imbalanced diabetic retinopathy severity classification
Diabetic Retinopathy (DR) is a retinal condition that leads to gradual degeneration of the retina and eventual blindness, so early detection and...
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Comprehensive review of retinal blood vessel segmentation and classification techniques: intelligent solutions for green computing in medical images, current challenges, open issues, and knowledge gaps in fundus medical images
Recently, there has been an advancement in the development of innovative computer-aided techniques for the segmentation and classification of retinal...
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Retinal Artery and Vein Segmentation Using an Image-to-Image Conditional Adversarial Network
With the continuous increasing advances in hardware, there is a growing interest in the automation of clinical processes. In this sense, retinal...
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Deep learning based diabetic retinopathy screening for resource constraint applications
Diabetic Retinopathy (DR) poses a critical health concern, affecting millions of individuals globally, particularly in light of the increasing...
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Blood vessel segmentation of retinal image using Clifford matched filter and Clifford convolution
The appearance and structure of blood vessels in retinal fundus image is a fundamental part of diagnosing different issues related with such as...
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A hybrid method for improving the luminosity and contrast of color retinal images using the JND model and multiple layers of CLAHE
Retinal imaging can be used to identify a variety of common eye and cardiac disorders. However, owing to non-uniform or poor illumination and low...
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Eye Diseases Classification Using Deep Learning
Eye disease recognition is a challenging task, which usually requires years of medical experience. In this work, we conducted research that can be a...
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Deep learning for diabetic retinopathy assessments: a literature review
Diabetic retinopathy (DR) is the most important complication of diabetes. Early diagnosis by performing retinal image analysis helps avoid visual...
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Construction of Retinal Vessel Segmentation Models Based on Convolutional Neural Network
Segmentation of retinal vessels in fundus images plays a very important role in diagnosing relevant diseases. In this paper, we have constructed...
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Exploring Eye Expressions for Enhancing EOG-Based Interaction
This paper explores the classification of eye expressions for EOG-based interaction using JINS MEME, an off-the-shelf eye-tracking device. Previous...
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Assessing vascular complexity of PAOD patients by deep learning-based segmentation and fractal dimension
The assessment of vascular complexity in the lower limbs provides relevant information about peripheral artery occlusive diseases (PAOD), thus...
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An Elastic Interaction-Based Loss Function for Medical Image Segmentation
Deep learning techniques have shown their success in medical image segmentation since they are easy to manipulate and robust to various types of...
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Eye diseases detection using deep learning with BAM attention module
With the changing lifestyle, a large population suffers from eye diseases such as glaucoma, cataract, and diabetic retinopathy. Therefore, timely...
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Medical Image Synthesis Using Generative Adversarial Networks
The diagnostic capabilities in medical imaging domain saw significant improvements triggered by advances in deep learning in the past few years. The...