title: Dynamic Programming Based Segmentation in Biomedical Imaging.
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.
authors.affiliation: Department of Mathematics and Computer Science, University of Münster, Münster, Germany.
authors.forename: Kathrin
authors.initials: K
authors.lastname: Ungru
authors.affiliation: Department of Mathematics and Computer Science, University of Münster, Münster, Germany; Cluster of Excellence EXC 1003, Cells in Motion, Münster, Germany.
authors.forename: Xiaoyi
authors.initials: X
authors.lastname: Jiang
keywords: Active contours; Contour detection; Dynamic programming; Energy minimization; Segmentation; Shortest path