Adaptive optics imaging allows us to visualize the living human retina with single-cell resolution. This has the potential to transform the way in which retinal diseases are diagnosed and monitored, as well as inform the development of new treatments for patients with eye disease, such as retinitis pigmentosa, age-related macular degeneration, glaucoma, and albinism.
While obtaining adaptive optics images has become routine, there is no standard, validated and robust software tool that can process and analyze these images, which severely limits the clinical appplicability of adaptive optics imaging. Here we propose to overcome this technology gap.
This is an engineering proposal, which are rarely supported by traditional grant mechanisms.
Our goal is to develop a set of open-source objective image analysis tools to understand how light-sensitive rod and cone photoreceptors are arranged on the retina (or the ‘photoreceptor mosaic’). We will leverage our extensive collaborative relationships with retinal imaging labs around the world to ensure the software developed is robust, user-friendly, and practical.
The Advanced Ocular Imaging Program has already succeeded at deploying hardware and software for acquiring image of the living retina, and this project is a natural extension of our mission to improve the clinical use of adaptive optics imaging tools.
We expect to be able to release the first version of this software 6 months after the receipt of funding.
The landscape of retinal disease research is changing rapidly. New treatment approaches are emerging, and it is critical that we develop sensitive, non-invasive biomarkers to correctly diagnose these conditions as well as monitor how well treatments are doing.
We have at our fingertips arguably the world's highest-resolution retinal imaging system, which allows us to image individual cells in the living human retina. However, because software tools with which to extract relevant information from these images are severely lacking, the open-source, validated software that will be developed in this project will benefit all research groups doing similar imaging work.
Medical College of Wisconsin