AIMC Topic: Retinal Vessels
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Retinal vessel segmentation using multi-scale textons derived from keypoints.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 22, 2015
This paper presents a retinal vessel segmentation algorithm which uses a texton dictionary to classify vessel/non-vessel pixels. However, in contrast to previous work where filter parameters are learnt from manually labelled image pixels our filter p...
Retinal vessel extraction using Lattice Neural Networks with Dendritic Processing.
Computers in biology and medicine
Dec 31, 2014
Retinal images can be used to detect and follow up several important chronic diseases. The classification of retinal images requires an experienced ophthalmologist. This has been a bottleneck to implement routine screenings performed by general physi...
Trainable COSFIRE filters for vessel delineation with application to retinal images.
Medical image analysis
Sep 3, 2014
Retinal imaging provides a non-invasive opportunity for the diagnosis of several medical pathologies. The automatic segmentation of the vessel tree is an important pre-processing step which facilitates subsequent automatic processes that contribute t...
Optical coherence tomography angiography as a tool for diagnosis and monitoring of sickle cell related eye disease: a systematic review and meta-analysis.
Eye (London, England)
Aug 1, 2025
Sickle cell retinopathy (SCR) is an ocular manifestation of sickle cell disease (SCD). In SCR abnormal sickling of erythrocytes is associated with sight-threatening complications such as neovascularisation, vitreous haemorrhage, maculopathy and retin...
MSPDD-net: Mamba semantic perception dual decoding network for retinal image vessel segmentation.
Computers in biology and medicine
Jul 1, 2025
In the Retinal Image Vessel (RIV) segmentation task, due to existing a large number of low-contrast capillaries in the image usually leads to the problem of poor segmentation accuracy. To address this issue, this study aims to fully model the global ...
AI Quantification of Vascular Lesions in Mouse Fundus Fluorescein Angiography.
Translational vision science & technology
Jun 2, 2025
PURPOSE: Quantifying vascular leakage in fundus fluorescein angiography (FFA) is a critical endpoint in preclinical models of diseases such as neovascular age-related macular degeneration, retinopathy of prematurity, and diabetic retinopathy. Traditi...
Joint high-resolution feature learning and vessel-shape aware convolutions for efficient vessel segmentation.
Computers in biology and medicine
Jun 1, 2025
Clear imagery of retinal vessels is one of the critical shreds of evidence in specific disease diagnosis and evaluation, including sophisticated hierarchical topology and plentiful-and-intensive capillaries. In this work, we propose a new topology- a...
Relationships Between Retinal Vascular Characteristics and Systemic Indicators in Patients With Diabetes Mellitus.
Investigative ophthalmology & visual science
Apr 1, 2025
PURPOSE: To develop a deep learning method for vessel segmentation in fundus images, measure retinal vessels, and study the connection between retinal vascular features and systemic indicators in diabetic patients.
Artificial Intelligence Versus Rules-Based Approach for Segmenting NonPerfusion Area in a DRCR Retina Network Optical Coherence Tomography Angiography Dataset.
Investigative ophthalmology & visual science
Mar 3, 2025
PURPOSE: Loss of retinal perfusion is associated with both onset and worsening of diabetic retinopathy (DR). Optical coherence tomography angiography is a noninvasive method for measuring the nonperfusion area (NPA) and has promise as a scalable scre...
Retinal Arteriovenous Information Improves the Prediction Accuracy of Deep Learning-Based baPWV Index From Color Fundus Photographs.
Investigative ophthalmology & visual science
Feb 3, 2025
PURPOSE: To compare the prediction accuracy of brachial-ankle pulse wave velocity (baPWV) from color fundus photographs (CFPs) using different deep learning models.
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