Retinal based Automated Healthcare Framework via Deep Learning

Abstract

Developing countries have limited access to low cost retinal images which hinders the progress in preventing needless blindness. Portable advancements are opening new doors to human services. Handheld ophthalmoscopes and smartphone fundus photography solutions are already providing promising solutions to low cost and portability. In this paper, we have discussed a new way to retinal fundus photography based on a Head Mounted Device(HMD) concept. HMDs will allow to obtain automated retinal images from patients. These images acts as biomarkers and helps in detection of chronic and long term diseases. Deep learning techniques are utilised to automate disease detection and patients are given corrective suggestions through their smartphones. We are translating technology into clinical care in the dawn of smart healthcare.