| Abstract |
Most blindness is the result of eye disease that develops throughout a person's lifetime. Although different diseases have different patterns, in general they are all responsible for causing some damage to the retina at the back of the eye that gradually spreads and increases in magnitude reducing visual function gradually over time. Early diagnosis is therefore essential for saving as much of the retina as possible and preventing blindness. Obtaining images of the retina is one of the tools used by clinicians to assess the retinal health and diagnose disease; but good, detailed images are very hard to obtain for optical and biological reasons. Complex retinal imaging systems have been developed over the past couple of decades to obtain better images of the retina and improve the success rate of diagnosis. This project proposes a novel technique to image the living human retina based on a technology developed in microscopy. By illuminating the retina with patterned light instead of an even illumination and performing mathematical transformations to the images obtained, it is possible to get good quality three-dimensional images of the retina in a manner simpler than with existing techniques and providing images that are more faithful to the real retina. Such a technique will enable more accurate screening, owing to the better image quality, and also wider screening of the population, since simple low-costs instruments are more likely to be wide-spread to high-street optometry clinics than expensive instrumentation.The project will design and develop a first prototype using this novel technique after studying, both theoretically and experimentally, various possible configurations for this device. The prototype will be then tested on a group of volunteers to assess its performance and it will be compared with existing commercial retinal imaging instrumentation. Possibilities for commercial exploitation and clinical collaborations will be considered throughout the project. This work will provide an ideal 3-year training programme for a PhD student. |
