Laser eye surgery is the most effective known procedure for treating choroidal neovascularization (CNV) found in a variety of conditions including age-related macular degeneration, histoplasmic choroiditis, etc. However, the current rate of success of this procedure is less than 50% for eradication of the CNV following one treatment session, with a recurrence and/or persistence rate of about 50%. This research will make possible an instrument that will drastically reduce this failure rate. The instrument consists of a computerized multi-spectral 3-D fundus camera with an associated head-up display and a real-time laser tracking system. The tracking system uses a set of automatic image analysis routines that allow accurate mapping of the pathologies, and computerized laser treatment planning. The core image-processing problems that are being addressed are: (i) constructing a wide-area map of the retinal vasculature from an image sequence; and (ii) determining the location of the current frame relative to the wide-area map constructed in step (i) to an accuracy of 2 pixels, or better, at a frame rate of at least 30 per second. The above problems are being solved by the development of a fast algorithm for matching point sets with unknown correspondences, in the presence of a small number of noise points. This algorithm operates by limiting the search to a minimally- sufficient subset of the most reliable image feature points. In addition, the proposed algorithm is being implemented on a linear array of processors, further enabling real-time operation.
