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An improved method for retinal vessel segmentation in U-Net
The utilization of retinal vessel images is prevalent in the diagnosis of numerous diseases, such as chronic vascular diseases, diabetic retinopathy,...
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Enhancing retinal fundus image classification through Active Gradient Deep Convolutional Neural Network and Red Spider Optimization
Retinal fundus image classification is pivotal for the early detection of various eye disorders. Leveraging advancements in deep learning, this...
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Segmentation of retinal blood vessel using generalized extreme value probability distribution function(pdf)-based matched filter approach
Retinal vessels’ segmentation is challenging to detect blood vessels for diagnosing diseases such as hypertension, diabetes, and glaucoma. Retinal...
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Noise reduction deep CNN-based retinal fundus image enhancement using recursive histogram
Retinal imaging often falls short in image quality due to limitations in imaging conditions. Issues such as low contrast and inadequate brightness...
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Human retinal optic disc detection with grasshopper optimization algorithm
A growing number of qualified ophthalmologists are promoting the need to use computer-based retinal eye processing image recognition technologies....
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IterMiUnet: A lightweight architecture for automatic blood vessel segmentation
The automatic segmentation of blood vessels in fundus images can help analyze the condition of retinal vasculature, which is crucial for identifying...
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PCRTAM-Net: A Novel Pre-Activated Convolution Residual and Triple Attention Mechanism Network for Retinal Vessel Segmentation
Retinal images play an essential role in the early diagnosis of ophthalmic diseases. Automatic segmentation of retinal vessels in color fundus images...
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Computer-aided diagnostic model for retinal vascular diseases using graph-based attention mechanism
Retinal vascular segmentation and classification plays a substantial role in predicting ocular pathologies in medical applications. This work aims in...
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NAUNet: lightweight retinal vessel segmentation network with nested connections and efficient attention
The state of retinal vessels in fundus images is a reliable biomarker for many diseases, and the accurate segmentation of retinal vessels is...
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Eye diseases diagnosis using deep learning and multimodal medical eye imaging
The present study carries out an empirical evaluation and comparison of the seven most recent deep Convolutional Neural Network (CNN) techniques...
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Curvilinear object segmentation in medical images based on ODoS filter and deep learning network
Automatic segmentation of curvilinear objects in medical images plays an important role in the diagnosis and evaluation of human diseases, yet it is...
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Detection and classification of red lesions from retinal images for diabetic retinopathy detection using deep learning models
Diabetic retinopathy (DR) is an eye disease caused by retinal damage induced by the long-term illness of diabetes mellitus. In the early stages, DR...
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Retinal vessel segmentation by using AFNet
Retinal vessel segmentation can obtain rich ocular information which is important for the diagnosis of fundus diseases. To address the problems of...
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Deep-learning based system for effective and automatic blood vessel segmentation from Retinal fundus images
The segmentation of blood vessels through color fundus images is a difficult and time-consuming task that requires experienced clinicians. Recently,...
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HRNet:A hierarchical recurrent convolution neural network for retinal vessel segmentation
The extraction of retinal vessel is of great importance in the diagnosis of fundus disease. Many approaches have been proposed for vessel...
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MixUNet: A Hybrid Retinal Vessels Segmentation Model Combining The Latest CNN and MLPs
The success of Vision Transformer has led to an increased emphasis on combining global and local context, and its high training cost spawned numerous...
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Analysis of retinal blood vessel segmentation techniques: a systematic survey
Segmentation of Blood Vessel is a challenging mission in medical image processing to diagnose the disease. It evaluates vessels crucial in automatic...
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Exudate and drusen classification in retinal images using bagged colour vector angles and inter colour local binary patterns
The presence of exudates is one of the most significant signs of Diabetic retinopathy (DR) whereas; white or tiny yellow deposits known as drusen...
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Diabetic Retinopathy Blood Vessel Detection Using Deep-CNN-Based Feature Extraction and Classification
Diabetic Retinopathy (DR) is the main cause of blindness and harms the retina due to the accumulation of glucose in the blood. Therefore, early DR...
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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...