This technology is a computer program that automatically detects and quantifies subtle changes in disease markers present in the human retina, resulting from diseases such as age-related macular degeneration (AMD) or diabetic retinopathy (DR). Current imaging methods to monitor and diagnose retinal diseases include fundus autoflourescence (FAF), fluorescein angiography (FA), indocyanine greene (IGC) imaging. The technology here applies digital image processing techniques to these commonly used imaging methods in order to provide automation, eliminate variability, and generate reliable quantifiable metrics. These qualities provide an advantage of this technology over currently available technologies.
Retinal disease prevalence and impact in the U.S.
Millions of Americans are at risk for vision impairment and blindness due to retinal diseases. For example, 1.8 million Americans aged 40 years and older are affected by AMD and 7.3 million are at substantial risk of developing the disease. DR affects approximately 5 million people in the U.S. and is the leading cause of blindness among Americans aged 20-74 years. The current prevalence of retinal diseases, combined with the expectation that the number of people affected by these diseases will increase in the future due to aging populations, underscore the necessity to provide health care professional with tools, like the technology here, that allow for rapid and easy identification and assessment of retinal disease progression.
- Digital processing of retinal imaging techniques
- Software identifies and assesses progression of retinal disease
- Automated and quantitative
- Eliminates subjective human interpretation