4D Motion Modeling: Estimation of Respiratory Motion for Radiation Therapy

Jan Ehrhardt; R. Werner; A. Schmidt-Richberg; H. Handels

doi:10.1007/978-3-642-03882-2_575

4D Motion Modeling: Estimation of Respiratory Motion for Radiation Therapy

Jan Ehrhardt, R. Werner, A. Schmidt-Richberg, H. Handels

Institute of Medical Informatics

Abstract

With 4D imaging techniques spatiotemporal image sequences can be acquired to investigate dynamic processes in the patient's body. However, 4-D images are not sufficient in themselves for motion measurement. Therefore, motion estimation algorithms have gained in importance in the last years. In this paper, the increasing role of image registration and motion estimation algorithms for the interpretation of complex 4D medical image sequences is illustrated. Two conceptually different motion estimation algorithms are presented and the clinical relevance is demonstrated by means of two example applications which are related to the radiation therapy of thoracic and abdominal tumors. Perspectives are shown by an insight into a current field of research: the statistical motion modeling.

Original language	English
Title of host publication	World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany
Number of pages	4
Volume	25/4
Place of Publication	Berlin, Heidelberg
Publisher	Springer Verlag
Publication date	01.12.2009
Pages	2166-2169
ISBN (Print)	978-3-642-03881-5
ISBN (Electronic)	978-3-642-03882-2
DOIs	https://doi.org/10.1007/978-3-642-03882-2_575
Publication status	Published - 01.12.2009
Event	World Congress on Medical Physics and Biomedical Engineering: Diagnostic Imaging - Munich , Germany Duration: 07.09.2009 → 12.09.2009 Conference number: 81644

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title = "4D Motion Modeling: Estimation of Respiratory Motion for Radiation Therapy",

abstract = "With 4D imaging techniques spatiotemporal image sequences can be acquired to investigate dynamic processes in the patient's body. However, 4-D images are not sufficient in themselves for motion measurement. Therefore, motion estimation algorithms have gained in importance in the last years. In this paper, the increasing role of image registration and motion estimation algorithms for the interpretation of complex 4D medical image sequences is illustrated. Two conceptually different motion estimation algorithms are presented and the clinical relevance is demonstrated by means of two example applications which are related to the radiation therapy of thoracic and abdominal tumors. Perspectives are shown by an insight into a current field of research: the statistical motion modeling.",

author = "Jan Ehrhardt and R. Werner and A. Schmidt-Richberg and H. Handels",

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Ehrhardt, J, Werner, R, Schmidt-Richberg, A & Handels, H 2009, 4D Motion Modeling: Estimation of Respiratory Motion for Radiation Therapy. in World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany . vol. 25/4, IFMBE Proceedings, Springer Verlag, Berlin, Heidelberg, pp. 2166-2169, World Congress on Medical Physics and Biomedical Engineering: Diagnostic Imaging, Munich , Bavaria, Germany, 07.09.09. https://doi.org/10.1007/978-3-642-03882-2_575

4D Motion Modeling: Estimation of Respiratory Motion for Radiation Therapy. / Ehrhardt, Jan; Werner, R.; Schmidt-Richberg, A. et al.
World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany . Vol. 25/4 Berlin, Heidelberg: Springer Verlag, 2009. p. 2166-2169 (IFMBE Proceedings).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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AB - With 4D imaging techniques spatiotemporal image sequences can be acquired to investigate dynamic processes in the patient's body. However, 4-D images are not sufficient in themselves for motion measurement. Therefore, motion estimation algorithms have gained in importance in the last years. In this paper, the increasing role of image registration and motion estimation algorithms for the interpretation of complex 4D medical image sequences is illustrated. Two conceptually different motion estimation algorithms are presented and the clinical relevance is demonstrated by means of two example applications which are related to the radiation therapy of thoracic and abdominal tumors. Perspectives are shown by an insight into a current field of research: the statistical motion modeling.

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4D Motion Modeling: Estimation of Respiratory Motion for Radiation Therapy

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