Retinal vessel segmentation to diagnose diabetic retinopathy using fundus images: A survey
Diabetes can cause damage to the retina's blood vessels in the eye leading to diabetic
retinopathy (DR). The images captured using a fundus camera are used to segment and …
retinopathy (DR). The images captured using a fundus camera are used to segment and …
A hybrid multilayered classification model with VGG-19 net for retinal diseases using optical coherence tomography images
Retinal diseases are most widely affected by various types of people without any proper
reason. Nowadays, many retinal diseases are identified by experts. Detecting retinal …
reason. Nowadays, many retinal diseases are identified by experts. Detecting retinal …
Latent Graph Attention for Enhanced Spatial Context
Global contexts in images are quite valuable in image-to-image translation problems.
Conventional attention-based and graph-based models capture the global context to a large …
Conventional attention-based and graph-based models capture the global context to a large …
A retinal vessel segmentation method based improved U-Net model
K Sun, Y Chen, Y Chao, J Geng, Y Chen - Biomedical Signal Processing …, 2023 - Elsevier
There are two problems in retinal blood vessel segmentation, which are the insufficient
segmentation of small vessels due to the complex curvature morphology of blood vessels …
segmentation of small vessels due to the complex curvature morphology of blood vessels …
Semi-supervised auto-encoder graph network for diabetic retinopathy grading
Y Li, Z Song, S Kang, S Jung, W Kang - IEEE Access, 2021 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) causes quite a few blindness worldwide, which can be refrained
by the timely diagnosis on retinal images. Recently, researches on deep learning-based …
by the timely diagnosis on retinal images. Recently, researches on deep learning-based …
Fundus image segmentation via hierarchical feature learning
S Guo - Computers in Biology and Medicine, 2021 - Elsevier
Abstract Fundus Image Segmentation (FIS) is an essential procedure for the automated
diagnosis of ophthalmic diseases. Recently, deep fully convolutional networks have been …
diagnosis of ophthalmic diseases. Recently, deep fully convolutional networks have been …
Ble-net: boundary learning and enhancement network for polyp segmentation
N Ta, H Chen, Y Lyu, T Wu - Multimedia Systems, 2023 - Springer
Automatic polyp segmentation can improve the accuracy of colonoscopy and plays a crucial
role in colorectal cancer prevention. However, existing U-shaped convolutional neural …
role in colorectal cancer prevention. However, existing U-shaped convolutional neural …
Playing against deep-neural-network-based object detectors: A novel bidirectional adversarial attack approach
In the fields of deep learning and computer vision, the security of object detection models
has received extensive attention. Revealing the security vulnerabilities resulting from …
has received extensive attention. Revealing the security vulnerabilities resulting from …
Ccs-unet: a cross-channel spatial attention model for accurate retinal vessel segmentation
Y Zhu, X Xu, X Zhang, M Jiang - Biomedical Optics Express, 2023 - opg.optica.org
Precise segmentation of retinal vessels plays an important role in computer-assisted
diagnosis. Deep learning models have been applied to retinal vessel segmentation, but the …
diagnosis. Deep learning models have been applied to retinal vessel segmentation, but the …
Attention mechanisms in medical image segmentation: A survey
Medical image segmentation plays an important role in computer-aided diagnosis. Attention
mechanisms that distinguish important parts from irrelevant parts have been widely used in …
mechanisms that distinguish important parts from irrelevant parts have been widely used in …