Application of the Kohonen network for automatic point correspondence in retinal images.

In this paper, an algorithm for automatic point correspondence is proposed towards retinal image registration. Given a pair of corresponding retinal images and a set of bifurcations or other salient points in one of the images, the algorithm detects effectively the set of corresponding points in the second image, by exploiting the properties of Kohonen's Self Organizing Maps and embedding them in a stochastic optimization procedure. The proposed algorithm was tested on 20 unimodal retinal pairs and the obtained results show an enhanced performance in terms of accuracy and robustness compared to the existing algorithm, on which it is based.