Multiscale and two-loop strategies for speeding up segmentation via dynamic programming
Davi Geiger, Alok Kumar Gupta · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
In this paper, we present two strategies for speeding up our dynamic programming (DP) algorithm, presented in this proceedings. The algorithm is used for image segmentation starting with user specified initial points. The main drawback of DP is the long computational time. Therefore, we present two suboptimal strategies: (i) a multiscale approach, where the solution at a coarse scale gets propagated to fine scales, and (ii) a two-loop approach for closed contours. Since the user selected points are allowed to move we, (a) fix, arbitrarily one point to be the initial as well as the end point, among the selected points that are allowed to move, (b) run DP, (c) interchange the fixed point, and (d) run DP again. Both approaches together yield a factor of 50 on the speed, though at the expense of losing the optimality characteristic. The results applied to MRI left and right ventricle detection, to angiograms artery detections, and CTA bone segmentation are of excellent quality when compared to using the full DP.