Accurate Extraction of Vessel Bifurcations and Crossovers

Branching and crossover points in neuronal/vascular structures are of special interest from the standpoint of biology and medicine [9, 63]. One such application is the early diagnosis of hypertension by measuring changes in select vascular branching and crossover regions [82, 114]. Another example is the study of early development of the retinal vasculature, and its evolution under various pathologies and applied conditions [39, 77, 80,97,112].

Branching and crossover points are also important from a purely image analysis standpoint. The locations of these points, if known to be stable, are valuable as features (i.e., landmarks) for image registration and mosaicing [32,33,43,124]. The pattern of angles of intersection can be used as landmark signatures [9,10, 22,23].

Crucial to the performance of image registration algorithms is the accuracy and repeatability with which vascular crossing and branching locations (landmarks) can be extracted, more so than their absolute location [9]. The landmarks, when placed in correspondence, constrain the image-to-image transformation that must be estimated to register the images. Of particular interest, landmark repeatability plays two crucial roles: to reduce the number of possible correspondences between two images and accurately initialize a

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