Klüppel M, Wang J, Bernecker D, Fischer P, Hornegger J (2014)
Publication Type: Conference contribution, Original article
Publication year: 2014
Publisher: Springer
Edited Volumes: Informatik aktuell
Series: Informatik aktuell
City/Town: Berlin Heidelberg
Pages Range: 132-137
Conference Proceedings Title: Bildverarbeitung für die Medizin 2014
Event location: Aachen
URI: http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2014/Klueppel14-OFT.pdf
DOI: 10.1007/978-3-642-54111-7_28
Feature point tracking and detection of X-ray images is challenging due to overlapping anatomical structures of different depths, which lead to low-contrast images. Tracking of motion in X-ray sequences can support many clinical applications like motion compensation or two- or three-dimensional registration algorithms. This paper is the first to evaluate the performance of several feature tracking and detection algorithms on artificial and real X-ray image sequences, which involve rigid motion as well as external disturbances. A stand-alone application has been developed to provide an overall test bench for all algorithms, realized by OpenCV implementations. Experiments show that the Karhunen Loeve Transform-based Tracker is the most consistent and effective tracking algorithm. Considering external disturbances, template matching provides the most sufficient results. Furthermore, the influence of feature point detection methods on tracking results is shown.
APA:
Klüppel, M., Wang, J., Bernecker, D., Fischer, P., & Hornegger, J. (2014). On Feature Tracking in X-Ray Images. In Bildverarbeitung für die Medizin 2014 (pp. 132-137). Aachen: Berlin Heidelberg: Springer.
MLA:
Klüppel, Moritz, et al. "On Feature Tracking in X-Ray Images." Proceedings of the Bildverarbeitung für die Medizin 2014, Aachen Berlin Heidelberg: Springer, 2014. 132-137.
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