Blood vessel segmentation algorithms—review of methods, datasets and evaluation metrics
Background Blood vessel segmentation is a topic of high interest in medical image analysis
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
Blood vessel segmentation methodologies in retinal images–a survey
MM Fraz, P Remagnino, A Hoppe… - Computer methods and …, 2012 - Elsevier
Retinal vessel segmentation algorithms are a fundamental component of automatic retinal
disease screening systems. This work examines the blood vessel segmentation …
disease screening systems. This work examines the blood vessel segmentation …
DUNet: A deformable network for retinal vessel segmentation
Automatic segmentation of retinal vessels in fundus images plays an important role in the
diagnosis of some diseases such as diabetes and hypertension. In this paper, we propose …
diagnosis of some diseases such as diabetes and hypertension. In this paper, we propose …
Recurrent residual convolutional neural network based on u-net (r2u-net) for medical image segmentation
Deep learning (DL) based semantic segmentation methods have been providing state-of-the-
art performance in the last few years. More specifically, these techniques have been …
art performance in the last few years. More specifically, these techniques have been …
Recurrent residual U-Net for medical image segmentation
Deep learning (DL)-based semantic segmentation methods have been providing state-of-
the-art performance in the past few years. More specifically, these techniques have been …
the-art performance in the past few years. More specifically, these techniques have been …
Dual encoder-based dynamic-channel graph convolutional network with edge enhancement for retinal vessel segmentation
Retinal vessel segmentation with deep learning technology is a crucial auxiliary method for
clinicians to diagnose fundus diseases. However, the deep learning approaches inevitably …
clinicians to diagnose fundus diseases. However, the deep learning approaches inevitably …
Joint segment-level and pixel-wise losses for deep learning based retinal vessel segmentation
Objective: Deep learning based methods for retinal vessel segmentation are usually trained
based on pixel-wise losses, which treat all vessel pixels with equal importance in pixel-to …
based on pixel-wise losses, which treat all vessel pixels with equal importance in pixel-to …
Segmenting retinal blood vessels with deep neural networks
P Liskowski, K Krawiec - IEEE transactions on medical imaging, 2016 - ieeexplore.ieee.org
The condition of the vascular network of human eye is an important diagnostic factor in
ophthalmology. Its segmentation in fundus imaging is a nontrivial task due to variable size of …
ophthalmology. Its segmentation in fundus imaging is a nontrivial task due to variable size of …
Lightweight attention convolutional neural network for retinal vessel image segmentation
Retinal vessel image is an important biological information that can be used for personal
identification in the social security domain, and for disease diagnosis in the medical domain …
identification in the social security domain, and for disease diagnosis in the medical domain …
A three-stage deep learning model for accurate retinal vessel segmentation
Automatic retinal vessel segmentation is a fundamental step in the diagnosis of eye-related
diseases, in which both thick vessels and thin vessels are important features for symptom …
diseases, in which both thick vessels and thin vessels are important features for symptom …