AIMC Topic: Retinal Vessels

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Microscopic retinal blood vessels detection and segmentation using support vector machine and K-nearest neighbors.

Microscopy research and technique Jan 17, 2022
The retina is the deepest layer of texture covering the rear of the eye, recorded by fundus images. Vessel detection and segmentation are useful in disease diagnosis. The retina's blood vessels could help diagnose maladies such as glaucoma, diabetic ...
Retina Retinal Vessels Support Vector Machine Fundus Oculi Algorithms Image Processing, Computer-Assisted
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Self-relabeling for noise-tolerant retina vessel segmentation through label reliability estimation.

BMC medical imaging Jan 12, 2022
BACKGROUND: Retinal vessel segmentation benefits significantly from deep learning. Its performance relies on sufficient training images with accurate ground-truth segmentation, which are usually manually annotated in the form of binary pixel-wise lab...
Image Processing, Computer-Assisted Artifacts Retinal Vessels Humans Deep Learning
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Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 13, 2021
Automatic segmentation methods are an important advancement in medical image analysis. Machine learning techniques, and deep neural networks in particular, are the state-of-the-art for most medical image segmentation tasks. Issues with class imbalanc...
Image Processing, Computer-Assisted Entropy Retinal Vessels Neural Networks, Computer Algorithms
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Multi-Label Classification Scheme Based on Local Regression for Retinal Vessel Segmentation.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
Segmenting small retinal vessels with width less than 2 pixels in fundus images is a challenging task. In this paper, in order to effectively segment the vessels, especially the narrow parts, we propose a local regression scheme to enhance the narrow...
Humans Deep Learning Image Processing, Computer-Assisted Computational Biology Neural Networks, Computer Algorithms Regression Analysis Retinal Vessels
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RFARN: Retinal vessel segmentation based on reverse fusion attention residual network.

PloS one Dec 3, 2021
Accurate segmentation of retinal vessels is critical to the mechanism, diagnosis, and treatment of many ocular pathologies. Due to the poor contrast and inhomogeneous background of fundus imaging and the complex structure of retinal fundus images, th...
Image Enhancement Retinal Vessels Humans Databases, Factual Neural Networks, Computer Fundus Oculi
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Deep Learning Image Analysis of Optical Coherence Tomography Angiography Measured Vessel Density Improves Classification of Healthy and Glaucoma Eyes.

American journal of ophthalmology Nov 13, 2021
PURPOSE: To compare convolutional neural network (CNN) analysis of en face vessel density images to gradient boosting classifier (GBC) analysis of instrument-provided, feature-based optical coherence tomography angiography (OCTA) vessel density measu...
Fluorescein Angiography Retinal Vessels Retinal Ganglion Cells Visual Fields Humans Glaucoma Deep Learning Intraocular Pressure Tomography, Optical Coherence
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Optical coherence tomography (OCT) angiolytics: a review of OCT angiography quantitative biomarkers.

Survey of ophthalmology Nov 5, 2021
Optical coherence tomography angiography (OCTA) provides a non-invasive method to obtain angiography of the chorioretinal vasculature leading to its recent widespread adoption. With a growing number of studies exploring the use of OCTA, various bioma...
Retinal Vessels Tomography, Optical Coherence Fluorescein Angiography Humans Artificial Intelligence Biomarkers Choroid
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Fundus image segmentation via hierarchical feature learning.

Computers in biology and medicine Oct 9, 2021
Fundus Image Segmentation (FIS) is an essential procedure for the automated diagnosis of ophthalmic diseases. Recently, deep fully convolutional networks have been widely used for FIS with state-of-the-art performance. The representative deep model i...
Neural Networks, Computer Fundus Oculi Retinal Vessels Deep Learning Image Processing, Computer-Assisted
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Gated Skip-Connection Network with Adaptive Upsampling for Retinal Vessel Segmentation.

Sensors (Basel, Switzerland) Sep 15, 2021
Segmentation of retinal vessels is a critical step for the diagnosis of some fundus diseases. To further enhance the performance of vessel segmentation, we propose a method based on a gated skip-connection network with adaptive upsampling (GSAU-Net)...
Image Processing, Computer-Assisted Fundus Oculi Retinal Vessels Neural Networks, Computer Algorithms
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Imaging and artificial intelligence for progression of age-related macular degeneration.

Experimental biology and medicine (Maywood, N.J.) Aug 18, 2021
Age-related macular degeneration (AMD) is a leading cause of severe vision loss. With our aging population, it may affect 288 million people globally by the year 2040. AMD progresses from an early and intermediate dry form to an advanced one, which m...
Macular Degeneration Retinal Vessels Female Aging Humans Computational Biology Biomarkers Algorithms Prognosis Visual Acuity Disease Progression Tomography, Optical Coherence Deep Learning
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