AIMC Topic: Retinal Vessels

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Sex determination using color fundus parameters in older adults of Kumejima population study.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie Mar 1, 2023
PURPOSE: Deep learning artificial intelligence can determine the sex using only fundus photographs. However, the factors used by deep learning to determine the sex are not visible. Therefore, the purpose of the study was to determine whether the sex ...
Aged Adult Male Artificial Intelligence Female Optic Disk Diagnostic Techniques, Ophthalmological Retinal Vessels Middle Aged Fundus Oculi Humans
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Automatic vessel crossing and bifurcation detection based on multi-attention network vessel segmentation and directed graph search.

Computers in biology and medicine Feb 15, 2023
Analysis of the vascular tree is the basic premise to automatically diagnose retinal biomarkers associated with ophthalmic and systemic diseases, among which accurate identification of intersection and bifurcation points is quite challenging but impo...
Image Processing, Computer-Assisted Fundus Oculi Retinal Vessels Retina Neural Networks, Computer Algorithms
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Developing a Novel Methodology by Integrating Deep Learning and HMM for Segmentation of Retinal Blood Vessels in Fundus Images.

Interdisciplinary sciences, computational life sciences Jan 7, 2023
Accurate segregation of retinal blood vessels network plays a crucial role in clinical assessments, treatments, and rehabilitation process. Owing to the presence of acquisition and instrumentation anomalies, precise tracking of vessels network is cha...
Neural Networks, Computer Algorithms Deep Learning Humans Retinal Vessels Image Processing, Computer-Assisted Fundus Oculi
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MC-UNet: Multimodule Concatenation Based on U-Shape Network for Retinal Blood Vessels Segmentation.

Computational intelligence and neuroscience Nov 3, 2022
Accurate retinal blood vessels segmentation is an important step in the clinical diagnosis of ophthalmic diseases. Many deep learning frameworks have come up for retinal blood vessels segmentation tasks. However, the complex vascular structure and un...
Retinal Vessels Neural Networks, Computer Image Processing, Computer-Assisted Algorithms Retina
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SFA-Net: Scale and Feature Aggregate Network for Retinal Vessel Segmentation.

Journal of healthcare engineering Oct 21, 2022
A U-Net-based network has achieved competitive performance in retinal vessel segmentation. Previous work has focused on using multilevel high-level features to improve segmentation accuracy but has ignored the importance of shallow-level features. In...
Humans Algorithms Retinal Vessels Image Processing, Computer-Assisted Neural Networks, Computer
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Do you need sharpened details? Asking MMDC-Net: Multi-layer multi-scale dilated convolution network for retinal vessel segmentation.

Computers in biology and medicine Oct 13, 2022
Convolutional neural networks (CNN), especially numerous U-shaped models, have achieved great progress in retinal vessel segmentation. However, a great quantity of global information in fundus images has not been fully explored. And the class imbalan...
Algorithms Image Processing, Computer-Assisted Fundus Oculi Neural Networks, Computer Retinal Vessels
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Deep Learning-Based Noise Reduction Improves Optical Coherence Tomography Angiography Imaging of Radial Peripapillary Capillaries in Advanced Glaucoma.

Current eye research Sep 22, 2022
PURPOSE: We applied deep learning-based noise reduction (NR) to optical coherence tomography-angiography (OCTA) images of the radial peripapillary capillaries (RPCs) in eyes with glaucoma and investigated the usefulness of this method as an objective...
Capillaries Visual Fields Angiography Retinal Vessels Glaucoma, Open-Angle Fluorescein Angiography Tomography, Optical Coherence Optic Disk Middle Aged Deep Learning Reproducibility of Results Aged Intraocular Pressure Male Cross-Sectional Studies Humans Glaucoma Female
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Atrous residual convolutional neural network based on U-Net for retinal vessel segmentation.

PloS one Aug 22, 2022
Extracting features of retinal vessels from fundus images plays an essential role in computer-aided diagnosis of diseases, such as diabetes, hypertension, and cerebrovascular diseases. Although a number of deep learning-based methods have been used i...
Neural Networks, Computer Algorithms Disease Progression Humans Fundus Oculi Diagnosis, Computer-Assisted Retinal Vessels Image Processing, Computer-Assisted
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Deep learning for quality assessment of optical coherence tomography angiography images.

Scientific reports Aug 12, 2022
Optical coherence tomography angiography (OCTA) is an emerging non-invasive technique for imaging the retinal vasculature. While there are many promising clinical applications for OCTA, determination of image quality remains a challenge. We developed...
Humans Deep Learning Tomography, Optical Coherence Neural Networks, Computer Fluorescein Angiography Retinal Vessels
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Diagnosing Diabetic Retinopathy in OCTA Images Based on Multilevel Information Fusion Using a Deep Learning Framework.

Computational and mathematical methods in medicine Aug 4, 2022
OBJECTIVE: As an extension of optical coherence tomography (OCT), optical coherence tomographic angiography (OCTA) provides information on the blood flow status at the microlevel and is sensitive to changes in the fundus vessels. However, due to the ...
Retinal Vessels Diabetes Mellitus Tomography, Optical Coherence Fluorescein Angiography Humans Diabetic Retinopathy Deep Learning
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