AIMC Topic: Fovea Centralis

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DeepFoveaNet: Deep Fovea Eagle-Eye Bioinspired Model to Detect Moving Objects.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Aug 10, 2021
Birds of prey especially eagles and hawks have a visual acuity two to five times better than humans. Among the peculiar characteristics of their biological vision are that they have two types of foveae; one shallow fovea used in their binocular visio...
Humans Video Recording Neural Networks, Computer Movement Algorithms Fovea Centralis Vision, Binocular Databases, Factual Eagles Animals Image Processing, Computer-Assisted Models, Biological
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Machine learning prediction of pathologic myopia using tomographic elevation of the posterior sclera.

Scientific reports Mar 26, 2021
Qualitative analysis of fundus photographs enables straightforward pattern recognition of advanced pathologic myopia. However, it has limitations in defining the classification of the degree or extent of early disease, such that it may be biased by s...
Sclera Axial Length, Eye Myopia, Degenerative Middle Aged Support Vector Machine Tomography, Optical Coherence Fundus Oculi Optic Disk Fovea Centralis Retrospective Studies Female Male Humans Biomarkers
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Foveal avascular zone segmentation in optical coherence tomography angiography images using a deep learning approach.

Scientific reports Jan 13, 2021
The purpose of this study was to introduce a new deep learning (DL) model for segmentation of the fovea avascular zone (FAZ) in en face optical coherence tomography angiography (OCTA) and compare the results with those of the device's built-in softwa...
Deep Learning Tomography, Optical Coherence Healthy Volunteers Image Interpretation, Computer-Assisted Diabetic Retinopathy Diagnostic Techniques, Ophthalmological Male Humans Neural Networks, Computer Fovea Centralis Angiography Middle Aged Retrospective Studies Case-Control Studies Female Aged Adult
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Grading of Foveal Hypoplasia Using Deep Learning on Retinal Fundus Images.

Translational vision science & technology May 1, 2025
PURPOSE: This study aimed to develop and evaluate a deep learning model for grading foveal hypoplasia using retinal fundus images.
Adolescent Child, Preschool Child Humans Male Retrospective Studies Infant Female Deep Learning Adult ROC Curve Fovea Centralis Tomography, Optical Coherence Eye Diseases, Hereditary Fundus Oculi Nystagmus, Congenital
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Integrating Machine Learning and Traditional Survival Analysis to Identify Key Predictors of Foveal Involvement in Geographic Atrophy.

Investigative ophthalmology & visual science May 1, 2024
PURPOSE: The purpose of this study was to investigate the incidence of foveal involvement in geographic atrophy (GA) secondary to age-related macular degeneration (AMD), using machine learning to assess the importance of risk factors.
Humans Machine Learning Retrospective Studies Aged, 80 and over Male Middle Aged Female Risk Factors Aged Fovea Centralis Geographic Atrophy Tomography, Optical Coherence Survival Analysis Incidence Fluorescein Angiography Follow-Up Studies Visual Acuity
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Improved SSD network for accurate detection of optic disc and fovea and application in excyclotropia screening.

Journal of the Optical Society of America. A, Optics, image science, and vision Jan 1, 2021
The detection of the optic disc (OD) and fovea is essential to many automatic diagnosis systems for retinal diseases. The single shot multibox detector (SSD) can generate predictions from feature maps of various resolutions, which has not been introd...
Sensitivity and Specificity Image Interpretation, Computer-Assisted Optic Disk Pattern Recognition, Automated Fovea Centralis Exotropia Algorithms Databases, Factual Humans Reproducibility of Results Neural Networks, Computer
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A parametric texture model based on deep convolutional features closely matches texture appearance for humans.

Journal of vision Oct 1, 2017
Our visual environment is full of texture-"stuff" like cloth, bark, or gravel as distinct from "things" like dresses, trees, or paths-and humans are adept at perceiving subtle variations in material properties. To investigate image features important...
Pattern Recognition, Visual Eye Movements Humans Photic Stimulation Neural Networks, Computer Fovea Centralis Visual Perception
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