A kernel ridge regression model for respiratory motion estimation in radiotherapy

Tobias Geimer; Adriana Birlutiu; Mathias Unberath; Oliver Taubmann; Christoph Bert; Andreas Maier

doi:10.1007/978-3-662-54345-0_38

A kernel ridge regression model for respiratory motion estimation in radiotherapy

Tobias Geimer
, Adriana Birlutiu
, Mathias Unberath
, Oliver Taubmann
, Christoph Bert
, Andreas Maier

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper discusses a kernel ridge regression (KRR) model for motion estimation in radiotherapy. Using KRR, dense internal motion fields are estimated from high-dimensional surrogates without the need for prior dimensionality reduction. We compare the proposed model to a related approach with dimensionality reduction in the form of principal component analysis and principle component regression. Evaluation was performed in a simulation study based on nine 4D CT patient data sets achieving a mean estimation error of 0.84 ± 0.21 mm for our approach.

Original language	English (US)
Title of host publication	Bildverarbeitung fur die Medizin 2017
Subtitle of host publication	Algorithmen – Systeme – Anwendungen - Proceedings des Workshops
Editors	Klaus Hermann Maier-Hein, Heinz Handels, Thomas Martin Deserno, Thomas Tolxdorff
Publisher	Kluwer Academic Publishers
Pages	155-160
Number of pages	6
ISBN (Print)	9783662543443
DOIs	https://doi.org/10.1007/978-3-662-54345-0_38
State	Published - 2017
Externally published	Yes
Event	Workshops on Image processing for the medicine, 2017 - Heidelberg, Germany Duration: Mar 12 2017 → Mar 14 2017

Publication series

Name	Informatik aktuell
ISSN (Print)	1431-472X

Conference

Conference	Workshops on Image processing for the medicine, 2017
Country/Territory	Germany
City	Heidelberg
Period	3/12/17 → 3/14/17

ASJC Scopus subject areas

Modeling and Simulation

Access to Document

10.1007/978-3-662-54345-0_38

Cite this

Geimer, T., Birlutiu, A., Unberath, M., Taubmann, O., Bert, C., & Maier, A. (2017). A kernel ridge regression model for respiratory motion estimation in radiotherapy. In K. H. Maier-Hein, H. Handels, T. M. Deserno, & T. Tolxdorff (Eds.), Bildverarbeitung fur die Medizin 2017: Algorithmen – Systeme – Anwendungen - Proceedings des Workshops (pp. 155-160). (Informatik aktuell). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-662-54345-0_38

A kernel ridge regression model for respiratory motion estimation in radiotherapy. / Geimer, Tobias; Birlutiu, Adriana; Unberath, Mathias et al.
Bildverarbeitung fur die Medizin 2017: Algorithmen – Systeme – Anwendungen - Proceedings des Workshops. ed. / Klaus Hermann Maier-Hein; Heinz Handels; Thomas Martin Deserno; Thomas Tolxdorff. Kluwer Academic Publishers, 2017. p. 155-160 (Informatik aktuell).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Geimer, T, Birlutiu, A, Unberath, M, Taubmann, O, Bert, C & Maier, A 2017, A kernel ridge regression model for respiratory motion estimation in radiotherapy. in KH Maier-Hein, H Handels, TM Deserno & T Tolxdorff (eds), Bildverarbeitung fur die Medizin 2017: Algorithmen – Systeme – Anwendungen - Proceedings des Workshops. Informatik aktuell, Kluwer Academic Publishers, pp. 155-160, Workshops on Image processing for the medicine, 2017, Heidelberg, Germany, 3/12/17. https://doi.org/10.1007/978-3-662-54345-0_38

Geimer T, Birlutiu A, Unberath M, Taubmann O, Bert C, Maier A. A kernel ridge regression model for respiratory motion estimation in radiotherapy. In Maier-Hein KH, Handels H, Deserno TM, Tolxdorff T, editors, Bildverarbeitung fur die Medizin 2017: Algorithmen – Systeme – Anwendungen - Proceedings des Workshops. Kluwer Academic Publishers. 2017. p. 155-160. (Informatik aktuell). doi: 10.1007/978-3-662-54345-0_38

Geimer, Tobias ; Birlutiu, Adriana ; Unberath, Mathias et al. / A kernel ridge regression model for respiratory motion estimation in radiotherapy. Bildverarbeitung fur die Medizin 2017: Algorithmen – Systeme – Anwendungen - Proceedings des Workshops. editor / Klaus Hermann Maier-Hein ; Heinz Handels ; Thomas Martin Deserno ; Thomas Tolxdorff. Kluwer Academic Publishers, 2017. pp. 155-160 (Informatik aktuell).

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A kernel ridge regression model for respiratory motion estimation in radiotherapy

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