AIMC Topic: Optic Disk
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A Retrospective Comparison of Deep Learning to Manual Annotations for Optic Disc and Optic Cup Segmentation in Fundus Photographs.
Translational vision science & technology
Jun 24, 2020
PURPOSE: Optic disc (OD) and optic cup (OC) segmentation are fundamental for fundus image analysis. Manual annotation is time consuming, expensive, and highly subjective, whereas an automated system is invaluable to the medical community. The aim of ...
WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images.
International journal of computer assisted radiology and surgery
May 22, 2020
PURPOSE: The cup-to-disc ratio (CDR), a clinical metric of the relative size of the optic cup to the optic disc, is a key indicator of glaucoma, a chronic eye disease leading to loss of vision. CDR can be measured from fundus images through the segme...
DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images.
Translational vision science & technology
Apr 15, 2020
PURPOSE: To remove blood vessel shadows from optical coherence tomography (OCT) images of the optic nerve head (ONH).
Efficacy for Differentiating Nonglaucomatous Versus Glaucomatous Optic Neuropathy Using Deep Learning Systems.
American journal of ophthalmology
Apr 2, 2020
PURPOSE: We sought to assess the performance of deep learning approaches for differentiating nonglaucomatous optic neuropathy with disc pallor (NGON) vs glaucomatous optic neuropathy (GON) on color fundus photographs by the use of image recognition.
A Deep-Learning Approach for Automated OCT En-Face Retinal Vessel Segmentation in Cases of Optic Disc Swelling Using Multiple En-Face Images as Input.
Translational vision science & technology
Mar 24, 2020
PURPOSE: In cases of optic disc swelling, segmentation of projected retinal blood vessels from optical coherence tomography (OCT) volumes is challenging due to swelling-based shadowing artifacts. Based on our hypothesis that simultaneously considerin...
Optic Disc and Cup Image Segmentation Utilizing Contour-Based Transformation and Sequence Labeling Networks.
Journal of medical systems
Mar 20, 2020
Optic disc (OD) and optic cup (OC) segmentation are important steps for automatic screening and diagnosing of optic nerve head abnormalities such as glaucoma. Many recent works formulated the OD and OC segmentation as a pixel classification task. How...
Discriminating glaucomatous and compressive optic neuropathy on spectral-domain optical coherence tomography with deep learning classifier.
The British journal of ophthalmology
Feb 25, 2020
BACKGROUND/AIMS: To assess the performance of a deep learning classifier for differentiation of glaucomatous optic neuropathy (GON) from compressive optic neuropathy (CON) based on ganglion cell-inner plexiform layer (GCIPL) and retinal nerve fibre l...
Domain-invariant interpretable fundus image quality assessment.
Medical image analysis
Jan 30, 2020
Objective and quantitative assessment of fundus image quality is essential for the diagnosis of retinal diseases. The major factors in fundus image quality assessment are image artifact, clarity, and field definition. Unfortunately, most of existing ...
Factors in Color Fundus Photographs That Can Be Used by Humans to Determine Sex of Individuals.
Translational vision science & technology
Jan 30, 2020
PURPOSE: Artificial intelligence (AI) can identify the sex of an individual from color fundus photographs (CFPs). However, the mechanism(s) involved in this identification has not been determined. This study was conducted to determine the information...
Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs.
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Jan 27, 2020
PURPOSE: To develop a deep learning approach based on deep residual neural network (ResNet101) for the automated detection of glaucomatous optic neuropathy (GON) using color fundus images, understand the process by which the model makes predictions, ...
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