Intensity-based 2D-3D registration using normalized gradient fields

Annkristin Lange; Stefan Heldmann

doi:10.1007/978-3-658-29267-6_33

Intensity-based 2D-3D registration using normalized gradient fields

Annkristin Lange^*, Stefan Heldmann

^*Korrespondierende/r Autor/-in für diese Arbeit

Institut für Mathematische Methoden der Bildverarbeitung

Abstract

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.

Originalsprache	Englisch
Titel	Bildverarbeitung für die Medizin 2020
Redakteure/-innen	Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm
Seitenumfang	6
Herausgeber (Verlag)	Springer Vieweg, Wiesbaden
Erscheinungsdatum	12.02.2020
Seiten	163-168
ISBN (Print)	978-3-658-29266-9
ISBN (elektronisch)	978-3-658-29267-6
DOIs	https://doi.org/10.1007/978-3-658-29267-6_33
Publikationsstatus	Veröffentlicht - 12.02.2020
Veranstaltung	Bildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen - Berlin, Deutschland Dauer: 15.03.2020 → 17.03.2020 Konferenznummer: 237969

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title = "Intensity-based 2D-3D registration using normalized gradient fields",

abstract = "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.",

author = "Annkristin Lange and Stefan Heldmann",

note = "Funding Information: Acknowledgement. This work was funded by the German Federal Ministry of Education and Research (BMBF, project NavEVAR, funding code: 13GW0228C). Publisher Copyright: {\textcopyright} Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; Bildverarbeitung f{\"u}r die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen<br/> ; Conference date: 15-03-2020 Through 17-03-2020",

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doi = "10.1007/978-3-658-29267-6_33",

language = "English",

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series = "Informatik aktuell",

publisher = "Springer Vieweg, Wiesbaden",

pages = "163--168",

editor = "Tolxdorff, {Thomas } and {M. Deserno}, {Thomas } and Handels, {Heinz } and Maier, {Andreas } and {H. Maier-Hein}, {Klaus } and Palm, {Christoph }",

booktitle = "Bildverarbeitung f{\"u}r die Medizin 2020",

}

Lange, A & Heldmann, S 2020, Intensity-based 2D-3D registration using normalized gradient fields. in T Tolxdorff, T M. Deserno, H Handels, A Maier, K H. Maier-Hein & C Palm (Hrsg.), Bildverarbeitung für die Medizin 2020 . Informatik aktuell, Springer Vieweg, Wiesbaden, S. 163-168, Bildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen
, Berlin, Berlin, Deutschland, 15.03.20. https://doi.org/10.1007/978-3-658-29267-6_33

Intensity-based 2D-3D registration using normalized gradient fields. / Lange, Annkristin; Heldmann, Stefan.
Bildverarbeitung für die Medizin 2020 . Hrsg. / Thomas Tolxdorff; Thomas M. Deserno; Heinz Handels; Andreas Maier; Klaus H. Maier-Hein; Christoph Palm. Springer Vieweg, Wiesbaden, 2020. S. 163-168 (Informatik aktuell).

Publikation: Kapitel in Büchern/Berichten/Konferenzbänden › Konferenzbeitrag › Begutachtung

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T1 - Intensity-based 2D-3D registration using normalized gradient fields

AU - Lange, Annkristin

AU - Heldmann, Stefan

N1 - Conference code: 237969

PY - 2020/2/12

Y1 - 2020/2/12

N2 - 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.

AB - 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.

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DO - 10.1007/978-3-658-29267-6_33

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SN - 978-3-658-29266-9

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BT - Bildverarbeitung für die Medizin 2020

A2 - Tolxdorff, Thomas

A2 - M. Deserno, Thomas

A2 - Handels, Heinz

A2 - Maier, Andreas

A2 - H. Maier-Hein, Klaus

A2 - Palm, Christoph

PB - Springer Vieweg, Wiesbaden

T2 - Bildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen<br/>

Y2 - 15 March 2020 through 17 March 2020

ER -

Intensity-based 2D-3D registration using normalized gradient fields

Abstract

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