Learning-based misalignment detection for 2-D/3-D overlays

Schaffert R, Wang J, Fischer P, Borsdorf A, Maier A (2020)

Publication Type: Conference contribution

Publication year: 2020

Journal

Informatik aktuell Gesellschaft für Informatik (GI)

Publisher: Springer

Pages Range: 230-235

Conference Proceedings Title: Informatik aktuell

Event location: Berlin DE

ISBN: 9783658292669

DOI: 10.1007/978-3-658-29267-6_52

Abstract

In minimally invasive procedures, a standard routine of observing the operational site is using image guidance. X-ray fluoroscopy using C-arm systems is widely used. In complex cases, overlays of preoperative 3-D images are necessary to show structures that are not visible in the 2-D X-ray images. The alignment quality may degenerate during an intervention, e. g. due to patient motion, and a new registration needs to be performed. However, a decrease in alignment quality is not always obvious, as the clinician often focuses on structures which are not visible in the 2-D image, and only these structures are visualized in the overlay. In this paper, we propose a learning-based method for detecting different degrees of misalignment. The method is based on point-to-plane correspondences and a pre-trained neural network originally used for detecting good correspondences. The network is extended by a classification branch to detect different levels of misalignment. Compared to simply using the normalized gradient correlation similarity measure as a basis for the decision, we show a highly improved performance, e. g. improving the AUC score from 0.918 to 0.993 for detecting misalignment above 5mm of mean re-projection distance.

Authors with CRIS profile

Roman Schaffert Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) (LME) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

How to cite

APA:

Schaffert, R., Wang, J., Fischer, P., Borsdorf, A., & Maier, A. (2020). Learning-based misalignment detection for 2-D/3-D overlays. In Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm (Eds.), Informatik aktuell (pp. 230-235). Berlin, DE: Springer.

MLA:

Schaffert, Roman, et al. "Learning-based misalignment detection for 2-D/3-D overlays." Proceedings of the International workshop on Algorithmen - Systeme - Anwendungen, 2020, Berlin Ed. Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm, Springer, 2020. 230-235.

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