Zusammenfassung
2D-3D registration is central to image guided minimal invasive endovascular therapies such as the treatment of aneurysms. We propose a novel intensity-based 2D-3D registration method based on digitally reconstructed radiographs and the so-called Normalized Gradient Fields (NGF) as a distance measure. We evaluate our method on publicly available clinical data and compare it to five other state-of-the-art 2D-3D registration methods. The results show that our method achieves better accuracy with comparable results in terms of the number of successful registrations and robustness.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
Literatur
Markelj P, Tomaževič D, Likar B, et al. A review of 3D/2D registration methods for image-guided interventions. Med Image Anal. 2012;16(3):642–61.
Goitein M, Abrams M, Rowell D, et al. Multi-dimensional treatment planning: II. Beam’s eye-view, back projection, and projection through CT sections. Int J Radiat Oncol Biol Phys. 1983;9(6):789 – 97.
Russakoff DB, Rohlfing T, Mori K, et al. Fast generation of digitally reconstructed radiographs using attenuation fields with application to 2D-3D image registration. IEEE Trans Med Imaging. 2005;24(11):1441–54.
Otake Y, Armand M, Armiger RS, et al. IEEE Trans Med Imaging. 2011;31(4):948–62.
Haber E, Modersitzki J. Intensity gradient based registration and fusion of multimodal images. In: Proc MiCCAI; 2006. p. 726–33.
Rühaak J, Heldmann S, Kipshagen T, et al. Highly accurate fast lung CT registration. In: SPIE Medical Imaging 2013: Image Processing; 2013.
Rühaak J, Polzin T, Heldmann S, et al. Estimation of large motion in lung CT by integrating regularized keypoint correspondences into dense deformable registration. IEEE Trans Med Imaging. 2017;36(8):1746–57.
Mitrović U, Pernuš F, Špiclin Ž, et al. 3D-2D registration of cerebral angiograms: a method and evaluation on clinical images. IEEE Trans Med Imaging. 2013;32(8):1550–63.
Mitrović U, Likar B, Pernuš F, et al. 3D–2D registration in endovascular imageguided surgery: evaluation of state-of-the-art methods on cerebral angiograms. Int J Comput Assist Radiol Surg. 2018;13(2):193–202.
Van de Kraats EB, Penney GP, Tomazevic D, et al. Standardized evaluation methodology for 2-D-3-D registration. IEEE Trans Med Imaging. 2005;24(9):1177–89.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
About this paper
Cite this paper
Lange, A., Heldmann, S. (2020). Intensity-Based 2D-3D Registration Using Normalized Gradient Fields. In: Tolxdorff, T., Deserno, T., Handels, H., Maier, A., Maier-Hein, K., Palm, C. (eds) Bildverarbeitung für die Medizin 2020. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-29267-6_33
Download citation
DOI: https://doi.org/10.1007/978-3-658-29267-6_33
Published:
Publisher Name: Springer Vieweg, Wiesbaden
Print ISBN: 978-3-658-29266-9
Online ISBN: 978-3-658-29267-6
eBook Packages: Computer Science and Engineering (German Language)