Congratulations to graduate student Skylar Stolte for her paper, ‘A Survey on Medical Image Analysis in Diabetic Retinopathy‘, now accepted for publication in Medical Image Analysis. Skyler has participated in many research projects after she joined the Smart Medical Informatics Learning and Evaluation lab (SMILE) under the mentorship of Dr. Ruogu Fang, assistant professor in the J. Crayton Pruitt Family Department of Biomedical Engineering and a member of the Warren B. Nelms Institute for the Connected World. Dr. Fang and the SMILE Lab’s research interests span across machine learning, data mining and medical/health computing.
Skyler and Dr. Ruogu’s paper focuses on developing highly accurate and efficient systems using artificial intelligence (AI) to help assist medical professionals in screening and diagnosing Diabetic Retinopathy (DR) earlier, while without the full resources that are available often only in specialty clinics. DR represents a highly-prevalent complication of diabetes in which individuals suffer from damage to the blood vessels in the retina. Retinal specialists strive to detect DR early so that the disease can be treated before substantial, irreversible vision loss occurs. This paper provides a comprehensive description of the detection of DR using deep learning systems that make decisions based on minimally handcrafted features and pave the way for personalized therapies. The proposed frameworks in the paper will facilitate early detection and classification of DR so as to prevent the invasive laser surgeries which might lead to vision loss if not detected in advance.