GA Based Registration of Temporal and Multimodal Occular Fundus Image Pairs

摘要

This paper describes how a Genetic Algorithms (GA) based optimization method is used specifically to register two ocular fundus images having either temporal or multimodal difference. Ocular fundus images of the same eye are generally compared by ophthalmologists to find differences due to growth of abnormalities in retina for diagnosis, follow-up, and surgery purposes. Being relatively small size and having different geometrical settings, comparison between these image pairs cannot be properly done without a registration first. In this paper, registration task is viewed as an optimization problem to search for optimal values of transformation parameters relating the two images. A GA based technique is applied to the preprocessed, binarized fundus image pair to find the best transformation which gives the maximum fitness for matching. A new formulation of fitness function is proposed to reduce computation time of GA while maintaining the required accuracy. Since the registration algorithm performance depends heavily on how well the image pair was preprocessed to obtain good quality binary images, the preprocessing methods are also explained in the paper. Results show that there is no performance difference for the proposed method when applied to either the temporal or the multimodal fundus image pair. The maximum, minimum, and average registration distances in pixels between the proposed method and manual method are 4.27, 1.83, and 3.18 respectively for the entire data set of 512x512 image pairs. The computation time is at least three times less than the method based on similar technique presented by another work.