In this small business innovations research (SBIR) project we present EyeArt, a retinal image analysis tool for automated diabetic retinopathy (DR) screenings with high diag- nostic efficacy.  With its interface to EyePACS, a license-free, scalable telemedicine plat- form, EyeArt will aid the expansion of DR screening and help bridge the exponentially growing disparity between the number of diabetic patients and the number of eye-care providers.  Research suggests that the Latino population in general are genetically predisposed to develop diabetes.  Their vulnerability to vision loss due to diabetic retinopathy is further compounded by factors such as lack of access to ophthalmology clinicians, lack of insurance, and lack of education.  According to the Department of Health Services (DHS) in Los Angeles County (LAC) the situation for diabetics is particularly grim, with current wait times upwards of 6-9 months for retinal examinations for retinopathy screening.  This can lead to treatment delays and progression towards irreversible vision loss.  To help reduce risk of vision loss in this diabetic population, we propose to use advanced image analysis algorithms in conjunction with existing telemedicine initiatives to enable faster screening, allow reprioritizatin of ophthalmologist appointments, and aid in triage of high-risk patients.  Our phase I prototype automatic DR screening tool has already shown great potential by beating current academic and commercial DR screening ap- proaches on large public retinal datasets.  Going forward, we will build on our approach and further develop innovative, customized algorithms for critical low-level image processing steps, while leveraging on recent advances in computer vision, and machine learning areas for high-level, inference steps to produce a clinical grade DR screening tool.  Our lesion localization and screening engine will be functionally integrated with EyePACS to further drive the expansion of screening, particularly benefiting under- resourced screening programs like the LAC-DHS safety net and its large Hispanic diabetic population.