Retinal vessel segmentation using deep learning: a review
This paper presents a comprehensive review of retinal blood vessel segmentation based on
deep learning. The geometric characteristics of retinal vessels reflect the health status of …
deep learning. The geometric characteristics of retinal vessels reflect the health status of …
A comprehensive review of deep learning strategies in retinal disease diagnosis using fundus images
In recent years, there has been an unprecedented growth in computer vision and deep
learning implementation owing to the exponential rise of computation infrastructure. The …
learning implementation owing to the exponential rise of computation infrastructure. The …
ResDO-UNet: A deep residual network for accurate retinal vessel segmentation from fundus images
For the clinical diagnosis, it is essential to obtain accurate morphology data of retinal blood
vessels from patients, and the morphology of retinal blood vessels can well help doctors to …
vessels from patients, and the morphology of retinal blood vessels can well help doctors to …
Bridge-Net: Context-involved U-net with patch-based loss weight mapping for retinal blood vessel segmentation
Retinal blood vessel segmentation in fundus images plays an important role in the early
diagnosis and treatment of retinal diseases. In recent years, the segmentation methods …
diagnosis and treatment of retinal diseases. In recent years, the segmentation methods …
Quadratic polynomial guided fuzzy C-means and dual attention mechanism for medical image segmentation
Medical image segmentation is the most complex and important task in the field of medical
image processing and analysis, as it is linked to disease diagnosis accuracy. However, due …
image processing and analysis, as it is linked to disease diagnosis accuracy. However, due …
Variation-aware federated learning with multi-source decentralized medical image data
Privacy concerns make it infeasible to construct a large medical image dataset by fusing
small ones from different sources/institutions. Therefore, federated learning (FL) becomes a …
small ones from different sources/institutions. Therefore, federated learning (FL) becomes a …
Global transformer and dual local attention network via deep-shallow hierarchical feature fusion for retinal vessel segmentation
Clinically, retinal vessel segmentation is a significant step in the diagnosis of fundus
diseases. However, recent methods generally neglect the difference of semantic information …
diseases. However, recent methods generally neglect the difference of semantic information …
SDDC-Net: A U-shaped deep spiking neural P convolutional network for retinal vessel segmentation
As an essential step in the early diagnosis of retinopathy, the blood vessels morphological
attributes assist specialists to obtain pathological information efficiently. Most existing deep …
attributes assist specialists to obtain pathological information efficiently. Most existing deep …
BCU-Net: Bridging ConvNeXt and U-Net for medical image segmentation
Medical image segmentation enables doctors to observe lesion regions better and make
accurate diagnostic decisions. Single-branch models such as U-Net have achieved great …
accurate diagnostic decisions. Single-branch models such as U-Net have achieved great …
A new deep learning method for blood vessel segmentation in retinal images based on convolutional kernels and modified U-Net model
ME Gegundez-Arias, D Marin-Santos… - Computer Methods and …, 2021 - Elsevier
Abstract Background and Objective: Automatic monitoring of retinal blood vessels proves
very useful for the clinical assessment of ocular vascular anomalies or retinopathies. This …
very useful for the clinical assessment of ocular vascular anomalies or retinopathies. This …