Laser photocoagulation is used to reduce vision loss due to degenerative eye conditions
by guiding a treatment laser over diseased tissue on the retina.
However, due to natural motions of the eye healthy retinal tissue can be damaged by the laser. Compensating for this motion can reduce this risk. Motion analysis of scanning
laser opthalmoscope (SLO) video provides information suitable for automatic laser aiming.
Motion estimation from SLO video can be achieved using landmark-based
motion tracking. In the ALET implementation, landmarks are manually
selected from a reference
This thesis work automates the landmark selection process in two steps:
first, a set of candidate landmarks is found using a corner detection
procedure on a vessel-enhanced retinal image; and second, the set of candidate
landmarks are ranked in decreasing order of their estimated tracking