Multiscale and "two-loop" strategies for speeding up segmentation via dynamic programming

Davi Geiger, Alok Gupta

Research output: Contribution to journalConference articlepeer-review


In this paper, we present two strategies for speeding up our dynamic programming (DP) algorithm, presented in this proceeding [3]. 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 allow 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.

Original languageEnglish (US)
Pages (from-to)766-772
Number of pages7
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - May 11 1994
EventMedical Imaging 1994: Image Processing - Newport Beach, United States
Duration: Feb 13 1994Feb 18 1994

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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