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 …
Developments in the detection of diabetic retinopathy: a state-of-the-art review of computer-aided diagnosis and machine learning methods
The exponential increase in the number of diabetics around the world has led to an equally
large increase in the number of diabetic retinopathy (DR) cases which is one of the major …
large increase in the number of diabetic retinopathy (DR) cases which is one of the major …
Full-resolution network and dual-threshold iteration for retinal vessel and coronary angiograph segmentation
Vessel segmentation is critical for disease diagnosis and surgical planning. Recently, the
vessel segmentation method based on deep learning has achieved outstanding …
vessel segmentation method based on deep learning has achieved outstanding …
Idrid: Diabetic retinopathy–segmentation and grading challenge
Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss,
predominantly affecting the working-age population across the globe. Screening for DR …
predominantly affecting the working-age population across the globe. Screening for DR …
VSSC Net: vessel specific skip chain convolutional network for blood vessel segmentation
PM Samuel, T Veeramalai - Computer methods and programs in …, 2021 - Elsevier
Background and objective Deep learning techniques are instrumental in develo** network
models that aid in the early diagnosis of life-threatening diseases. To screen and diagnose …
models that aid in the early diagnosis of life-threatening diseases. To screen and diagnose …
Simple methods for the lesion detection and severity grading of diabetic retinopathy by image processing and transfer learning
A Sugeno, Y Ishikawa, T Ohshima… - Computers in Biology and …, 2021 - Elsevier
Diabetic retinopathy (DR) has become one of the major causes of blindness. Due to the
increased prevalence of diabetes worldwide, diabetic patients exhibit high probabilities of …
increased prevalence of diabetes worldwide, diabetic patients exhibit high probabilities of …
Microaneurysm detection using fully convolutional neural networks
Abstract Backround and Objectives Diabetic retinopathy is a microvascular complication of
diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the …
diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the …
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 …
Blood vessel segmentation from fundus image by a cascade classification framework
Accurate segmentation of retinal vessel from fundus image is a prerequisite for the computer-
aided diagnosis of ophthalmology diseases. In this paper, we propose a novel and robust …
aided diagnosis of ophthalmology diseases. In this paper, we propose a novel and robust …
A systematic review on diabetic retinopathy detection using deep learning techniques
Segmentation is an essential requirement to accurately access diabetic retinopathy (DR)
and it becomes extremely time-consuming and challenging to detect manually. As a result …
and it becomes extremely time-consuming and challenging to detect manually. As a result …