AxoNet 2.0: A Deep Learning-Based Tool for Morphometric Analysis of Retinal Ganglion Cell Axons.

Purpose: Assessment of glaucomatous damage in animal models is facilitated by rapid and accurate quantification of retinal ganglion cell (RGC) axonal loss and morphologic change. However, manual assessment is extremely time- and labor-intensive. Here, we developed AxoNet 2.

Evaluation of Spatially Targeted Scleral Stiffening on Neuroprotection in a Rat Model of Glaucoma.

Purpose: Scleral stiffening may protect against glaucomatous retinal ganglion cell (RGC) loss or dysfunction associated with ocular hypertension. Here, we assess the potential neuroprotective effects of two treatments designed to stiffen either the entire posterior sclera or only the sclera adjacent to the peripapillary sclera in an experimental model of glaucoma.

Methods: Rat sclerae were stiffened in vivo using either genipin (crosslinking the entire posterior sclera) or a regionally selective photosensitizer, methylene blue (stiffening only the juxtaperipapillary region surrounding the optic nerve).

Assessment of Visual and Retinal Function Following In Vivo Genipin-Induced Scleral Crosslinking.

Purpose: Genipin has been proposed as a possible neuroprotective therapy in myopia and glaucoma. Here, we aim to determine the effects of prolonged genipin-induced scleral stiffening on visual function.

Methods: Eyes from Brown Norway rats were treated in vivo with either a single 15 mM genipin retrobulbar injection or sham retrobulbar injection and were compared to naïve eyes.

AxoNet: A deep learning-based tool to count retinal ganglion cell axons.

In this work, we develop a robust, extensible tool to automatically and accurately count retinal ganglion cell axons in optic nerve (ON) tissue images from various animal models of glaucoma. We adapted deep learning to regress pixelwise axon count density estimates, which were then integrated over the image area to determine axon counts. The tool, termed AxoNet, was trained and evaluated using a dataset containing images of ON regions randomly selected from whole cross sections of both control and damaged rat ONs and manually annotated for axon count and location.