Abstract
Many applications in biomedical imaging have a demand on automatic detection of lines, contours, or boundaries of bones, organs, vessels, and cells. Aim is to support expert decisions in interactive applications or to include it as part of a processing pipeline for automatic image analysis. Biomedical images often suffer from noisy data and fuzzy edges. Therefore, there is a need for robust methods for contour and line detection. Dynamic programming is a popular technique that satisfies these requirements in many ways. This work gives a brief overview over approaches and applications that utilize dynamic programming to solve problems in the challenging field of biomedical imaging.
Highlights
Dynamic Programming (DP) introduced by Richard Bellman [1] is a widely used technique to solve optimization problems in a simple and efficient way
Amini et al [2] showed on the example of active contours how DP can be utilized to perform energy minimization
As last method we present a region growing algorithm based on DP proposed in [22]
Summary
Dynamic Programming (DP) introduced by Richard Bellman [1] is a widely used technique to solve optimization problems in a simple and efficient way. DP was used to detect lines in images [3] especially in the field of road detection in satellite images for example by Merlet and Zerubia [4], while Buckley and Yang [5] applied DP to solve a shortest path (SP) problem. In biomedical imaging DP is a popular technique to find contours, lines and boundaries of organs, bones, vessels and cells. This survey focuses on applications in the field of biomedical imaging in particular on the detection and tracking of contours and structures by means of DP.
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