Dynamic Programming Based Segmentation in Biomedical Imaging

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. Biomedic...

Verfasser: Ungru, Kathrin
Jiang, Xiaoyi
Dokumenttypen:Artikel
Medientypen:Text
Erscheinungsdatum:2017
Publikation in MIAMI:26.04.2018
Datum der letzten Änderung:16.04.2019
Angaben zur Ausgabe:[Electronic ed.]
Quelle:Computational and Structural Biotechnology Journal 15 (2017), 255–264
Schlagwörter:Dynamic programming; Active contours; Energy minimization; Shortest path; Segmentation; Contour detection
Fachgebiet (DDC):000: Informatik, Wissen, Systeme
Lizenz:CC BY 4.0
Sprache:English
Förderung:Finanziert durch den Open-Access-Publikationsfonds 2017 der Westfälischen Wilhelms-Universität Münster (WWU Münster).
Format:PDF-Dokument
URN:urn:nbn:de:hbz:6-48189534573
Weitere Identifikatoren:DOI: http://dx.doi.org/10.1016/j.csbj.2017.02.001
Permalink:https://nbn-resolving.de/urn:nbn:de:hbz:6-48189534573
Onlinezugriff:2017_artikel_jiang.pdf

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.