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The Problem

In the USA and Canada, diabetes affects over 9% of the population.

The majority of diabetes patients will develop gradual loss of vision over the course of the disease – a condition termed Diabetic Retinopathy.


Diabetic retinopathy is caused by abnormalities in the blood vessels of the retina. Ophthalmologists can identify these abnormalities in a test called Fluorescein Angiography.

However, today the interpretation of Fluorescein Angiography still requires ophthalmologists to manually inspect the many images generated in each test.


This results in a procedure that is:

  • Time-consuming

  • Qualitative and subjective

  • Only as good as the human eye


RETICAD addresses this technological gap to facilitate reliable identification of patients who can benefit from therapeutic interventions (e.g., laser photocoagulation and anti-VEGF eye injections) that can limit the development of vision loss.


RETICAD uses sophisticated mathematical analysis, image-processing algorithms, and artificial intelligence to detect the 3 hallmarks of diabetic retinopathy ophthalmologists search for:

  1. Retinal microaneurysms

  2. Leaky blood vessels in the retina

  3. Retinal tissue with lack of blood supply


The patented technology uses the dynamics within the images to produce rapid, objective, quantitative and reliable results.

The utility of RETICAD was first demonstrated in 2013 (Serlin et al. PLoSONE, 2013), in a study showing that the software dramatically improves the diagnostic consensus between retinal experts.

Today, the RETICAD software is available as an online platform. Ophthalmologist can easily upload data to a secure server, and view/download maps that detail the health of retinal vasculature in a quantitative and objective manner. The software also allows precise tracking of disease progression and response to treatment.


By automating the manual interpretation of Fluorescein Angiography tests, RETICAD enables:

  • Earlier diagnosis of diabetic retinopathy and timely treatment

  • Precise follow-up of patients with diabetic retinopathy, and evaluation of treatment efficacy



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