I-Corps: TEAMS-MobileVision from Advanced Vision Labs

William Marsh Rice University, Houston TX

Investigators

Abstract

Age-related macular degeneration (AMD) is a disease of the eye that is the leading cause of central vision loss in people over 50 in the US. The progress of the disease can often be unpredictable and rapid. Existing technologies (bolted to tables, bulky, operated by clinician) can evaluate AMD during clinic visits, but such visits are scheduled only once every few months. Existing clinical practices fail to detect degeneration in-between clinic visits and leave clinicians and patients guessing. This I-Corps team proposes to take advantage of the ever-growing ubiquity of camera-enabled smartphones coupled with the rapid development of computational imaging to solve the between-visit AMD progression problem and usher in a new generation of portable, low-cost, computational eye-imaging devices. The development of the mobileVision AMD imager will increase understanding of how AMD progresses and how well treatments are performing by capturing retinal images at a time scale of days rather than months. These images, coupled with their review by doctors, will enable new research directions for automatic AMD diagnosis, and may lead to the development of new, more effective clinical practices. The proposed innovation is a take-home retinal imaging system. The physician shows the patient how to use the device during a scheduled visit, and then sends the patient home with the device. The patient then uses the device to take images of his or her own retina(s). The images are automatically sent to the physician, and they can be reviewed at his or her leisure. If the patient's AMD is progressing unusually, as indicated by the images, then the doctor informs the patient, and suggests an earlier follow-up visit. The fundamental research performed under previous awards demonstrates methodologies for acquiring retinal images easily, reliably, repeatably, and with high quality from a portable retinal imaging system. This directly enables the proposed implementation of a take-home retinal imaging device.