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Variational Registration

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Variational Registration : A Flexible Open-Source ITK Toolbox for Nonrigid Image Registration. / Ehrhardt, Jan; Schmidt-Richberg, Alexander; Werner, Rene; Handels, Heinz.

Bildverarbeitung für die Medizin 2015. ed. / Heinz Handels; Thomas Martin Deserno; Hans-Peter Meinzer; Thomas Tolxdorff. 1. ed. Berlin Heidelberg : Springer, 2015. p. 209-214 (Informatik Aktuell).

Research output: SCORING: Contribution to book/anthology › SCORING: Contribution to collected editions/anthologies › Research › peer-review

Harvard

Ehrhardt, J, Schmidt-Richberg, A, Werner, R & Handels, H 2015, Variational Registration: A Flexible Open-Source ITK Toolbox for Nonrigid Image Registration. in H Handels, TM Deserno, H-P Meinzer & T Tolxdorff (eds), Bildverarbeitung für die Medizin 2015. 1 edn, Informatik Aktuell, Springer, Berlin Heidelberg, pp. 209-214. https://doi.org/10.1007/978-3-662-46224-9_37

APA

Ehrhardt, J., Schmidt-Richberg, A., Werner, R., & Handels, H. (2015). Variational Registration: A Flexible Open-Source ITK Toolbox for Nonrigid Image Registration. In H. Handels, T. M. Deserno, H-P. Meinzer, & T. Tolxdorff (Eds.), Bildverarbeitung für die Medizin 2015 (1 ed., pp. 209-214). (Informatik Aktuell). Springer. https://doi.org/10.1007/978-3-662-46224-9_37

Vancouver

Ehrhardt J, Schmidt-Richberg A, Werner R, Handels H. Variational Registration: A Flexible Open-Source ITK Toolbox for Nonrigid Image Registration. In Handels H, Deserno TM, Meinzer H-P, Tolxdorff T, editors, Bildverarbeitung für die Medizin 2015. 1 ed. Berlin Heidelberg: Springer. 2015. p. 209-214. (Informatik Aktuell). https://doi.org/10.1007/978-3-662-46224-9_37

Bibtex

@inbook{db73821cf3174ba2b730a4a2e4e4c1d1,
title = "Variational Registration: A Flexible Open-Source ITK Toolbox for Nonrigid Image Registration",
abstract = "In this article, we present the flexible open-source toolbox “VariationalRegistration” for non-parametric variational image registration, realized as a module in the Insight segmentation and registration toolkit. The toolbox is designed to test, evaluate and systematically compare the effects of different building blocks of variational registration approaches, i.e. the distance/similarity measure, the regularization method and the transformation model. In its current state, the framework includes implementations of different similarity measures and regularization methods, as well as displacement-based and diffeomorphic transformation models. The implementation of further components is possible and encouraged. The implemented algorithms were applied to different registration problems and extensively tested using publicly accessible image data bases. This paper presents a quantitative evaluation for inter-patient registration using 3D brain MR images of the LONI image data base. The results demonstrate that the implemented variational registration scheme is competitive with other state-of-the-art approaches for non-rigid image registration.",
author = "Jan Ehrhardt and Alexander Schmidt-Richberg and Rene Werner and Heinz Handels",
year = "2015",
doi = "10.1007/978-3-662-46224-9_37",
language = "English",
isbn = "978-3-662-46223-2",
series = "Informatik Aktuell",
publisher = "Springer",
pages = "209--214",
editor = "Heinz Handels and Deserno, {Thomas Martin} and Hans-Peter Meinzer and Thomas Tolxdorff",
booktitle = "Bildverarbeitung f{\"u}r die Medizin 2015",
address = "Germany",
edition = "1",

}

RIS

TY - CHAP

T1 - Variational Registration

T2 - A Flexible Open-Source ITK Toolbox for Nonrigid Image Registration

AU - Ehrhardt, Jan

AU - Schmidt-Richberg, Alexander

AU - Werner, Rene

AU - Handels, Heinz

PY - 2015

Y1 - 2015

N2 - In this article, we present the flexible open-source toolbox “VariationalRegistration” for non-parametric variational image registration, realized as a module in the Insight segmentation and registration toolkit. The toolbox is designed to test, evaluate and systematically compare the effects of different building blocks of variational registration approaches, i.e. the distance/similarity measure, the regularization method and the transformation model. In its current state, the framework includes implementations of different similarity measures and regularization methods, as well as displacement-based and diffeomorphic transformation models. The implementation of further components is possible and encouraged. The implemented algorithms were applied to different registration problems and extensively tested using publicly accessible image data bases. This paper presents a quantitative evaluation for inter-patient registration using 3D brain MR images of the LONI image data base. The results demonstrate that the implemented variational registration scheme is competitive with other state-of-the-art approaches for non-rigid image registration.

AB - In this article, we present the flexible open-source toolbox “VariationalRegistration” for non-parametric variational image registration, realized as a module in the Insight segmentation and registration toolkit. The toolbox is designed to test, evaluate and systematically compare the effects of different building blocks of variational registration approaches, i.e. the distance/similarity measure, the regularization method and the transformation model. In its current state, the framework includes implementations of different similarity measures and regularization methods, as well as displacement-based and diffeomorphic transformation models. The implementation of further components is possible and encouraged. The implemented algorithms were applied to different registration problems and extensively tested using publicly accessible image data bases. This paper presents a quantitative evaluation for inter-patient registration using 3D brain MR images of the LONI image data base. The results demonstrate that the implemented variational registration scheme is competitive with other state-of-the-art approaches for non-rigid image registration.

U2 - 10.1007/978-3-662-46224-9_37

DO - 10.1007/978-3-662-46224-9_37

M3 - SCORING: Contribution to collected editions/anthologies

SN - 978-3-662-46223-2

T3 - Informatik Aktuell

SP - 209

EP - 214

BT - Bildverarbeitung für die Medizin 2015

A2 - Handels, Heinz

A2 - Deserno, Thomas Martin

A2 - Meinzer, Hans-Peter

A2 - Tolxdorff, Thomas

PB - Springer

CY - Berlin Heidelberg

ER -