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The Three-Dimensional Structural Configuration of the Central Retinal Vessel Trunk and Branches as a Glaucoma Biomarker
Our work also suggested that the major retinal blood vessels form a skeleton -- the configuration of which may be representative of major ONH structural changes as typically observed with the development and progression of glaucoma.
Describing the Structural Phenotype of the Glaucomatous Optic Nerve Head Using Artificial Intelligence
We argue this is because the vast amount of information available in a 3D OCT scan of the ONH has not been fully exploited.
Towards Label-Free 3D Segmentation of Optical Coherence Tomography Images of the Optic Nerve Head Using Deep Learning
Since the introduction of optical coherence tomography (OCT), it has been possible to study the complex 3D morphological changes of the optic nerve head (ONH) tissues that occur along with the progression of glaucoma.
DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images
Image quality was assessed qualitatively (for artifacts) and quantitatively using the intralayer contrast: a measure of shadow visibility ranging from 0 (shadow-free) to 1 (strong shadow) and compared to compensated images.
A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head
For all the ONH tissues, the mean CNR increased from $3. 50 \pm 0. 56$ (single-frame) to $7. 63 \pm 1. 81$ (denoised).
DRUNET: A Dilated-Residual U-Net Deep Learning Network to Digitally Stain Optic Nerve Head Tissues in Optical Coherence Tomography Images
Given that the neural and connective tissues of the optic nerve head (ONH) exhibit complex morphological changes with the development and progression of glaucoma, their simultaneous isolation from optical coherence tomography (OCT) images may be of great interest for the clinical diagnosis and management of this pathology.
