The methods of active contours ("snakes") and level sets were applied to images of the retina in order to locate the outer boundary of the optic disk. A gradient-vector-flow based active contour was used as it performed well over a large range of initial conditions. Images were pre-processed to lessen the influence of blood vessels on boundary detection. Both active contours and level set methods accurately located the correct boundary; level set methods were computationally more intensive.

No abstract

We describe a class of multiscale stochastic processes based on stochastic context-free grammars and called spatial random trees (SRTs) which can be effectively used for modeling multidimensional signals. In addition to modeling images which are sampled on a regular rectangular grid, we generalize this methodology to images defined on arbitraly graph structures. We develop likelihood calculation, MAP estimation, and EM-based parameter estimation algorithms for SRTs. To illustrate these methods, we apply them to classification of natural images using region graphs extracted by a recursive bipartitioning segmentation algorithm. 407

No abstract