Adaptive Optics (AO) retinal imaging has provided revolutionary tools to scientists and
clinicians for studying retinal structure and function in the living eye. From animal models to …

Adaptive optics scanning light ophthalmoscopy (AOSLO) allows visualization of the living
human retina with exquisite single-cell resolution. This technology has improved our …

Purpose: To develop an automated method of localizing and discerning multiple types of
findings in retinal images using a limited set of training data without hard-coded feature …

Deep learning strategies, particularly convolutional neural networks (CNNs), are especially
suited to finding patterns in images and using those patterns for image classification. The …

The local connection characteristics of convolutional neural network (CNN) are linked with
the local spatial correlation of image pixels for water depth retrieval in this article. The …

The foveated architecture of the human retina and the eye's mobility enables prime spatial
vision, yet the interplay between photoreceptor cell topography and the constant motion of …

Adaptive optics-optical coherence tomography (AO-OCT) allows for the three-dimensional
visualization of retinal ganglion cells (RGCs) in the living human eye. Quantitative analyses …

Photoreceptor ellipsoid zone (EZ) defects visible on optical coherence tomography (OCT)
are important imaging biomarkers for the onset and progression of macular diseases. As …

The small physical depression of the human retina, the fovea, is the retinal locus of prime
visual resolution, achieved by a peaking topography of the light-sensitive cone …

Purpose: To investigate retinal structure in subjects with CNGA3-associated achromatopsia
and evaluate disease symmetry and intrafamilial variability. Methods: Thirty-eight …