A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences

Jan Ehrhardt; Alexander Schmidt-Richberg; Heinz Handels

doi:10.1109/ICCV.2007.4409148

A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences

Jan Ehrhardt, Alexander Schmidt-Richberg, Heinz Handels

Institute of Medical Informatics

10 Citations (Scopus)

Abstract

In this paper a variational approach for the combined segmentation and registration of temporal image sequences is presented. The purpose of the proposed method is to estimate respiratory-induced organ motion in temporal CT image sequences and to segment a structure of interest simultaneously. In this model the segmentation of all images in the sequences is obtained by finding a non-linear registration to an initial segmentation in a reference image. A dense non-linear displacement field is estimated using image intensities and segmentation information in the images. Both problems (registration and segmentation) are formulated in a joint variational approach and solved simultaneously. A validation of the combined registration and segmentation approach is presented and demonstrates that the simultaneous solution of both problems improves the segmentation performance over a sequential application of the registration and segmentation steps.

Original language	English
Title of host publication	2007 IEEE 11th International Conference on Computer Vision
Number of pages	7
Publisher	IEEE
Publication date	01.12.2007
Pages	1-7
Article number	4409148
ISBN (Print)	978-1-4244-1630-1, 978-1-4244-1631-8
DOIs	https://doi.org/10.1109/ICCV.2007.4409148
Publication status	Published - 01.12.2007
Event	2007 IEEE 11th International Conference on Computer Vision - Rio de Janeiro, Brazil Duration: 14.10.2007 → 21.10.2007 Conference number: 73231

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Ehrhardt, J., Schmidt-Richberg, A., & Handels, H. (2007). A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences. In 2007 IEEE 11th International Conference on Computer Vision (pp. 1-7). Article 4409148 (Proceedings of the IEEE International Conference on Computer Vision). IEEE. https://doi.org/10.1109/ICCV.2007.4409148

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title = "A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences",

abstract = "In this paper a variational approach for the combined segmentation and registration of temporal image sequences is presented. The purpose of the proposed method is to estimate respiratory-induced organ motion in temporal CT image sequences and to segment a structure of interest simultaneously. In this model the segmentation of all images in the sequences is obtained by finding a non-linear registration to an initial segmentation in a reference image. A dense non-linear displacement field is estimated using image intensities and segmentation information in the images. Both problems (registration and segmentation) are formulated in a joint variational approach and solved simultaneously. A validation of the combined registration and segmentation approach is presented and demonstrates that the simultaneous solution of both problems improves the segmentation performance over a sequential application of the registration and segmentation steps.",

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Ehrhardt, J, Schmidt-Richberg, A & Handels, H 2007, A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences. in 2007 IEEE 11th International Conference on Computer Vision., 4409148, Proceedings of the IEEE International Conference on Computer Vision, IEEE, pp. 1-7, 2007 IEEE 11th International Conference on Computer Vision , Rio de Janeiro, Brazil, 14.10.07. https://doi.org/10.1109/ICCV.2007.4409148

A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences. / Ehrhardt, Jan; Schmidt-Richberg, Alexander; Handels, Heinz.
2007 IEEE 11th International Conference on Computer Vision. IEEE, 2007. p. 1-7 4409148 (Proceedings of the IEEE International Conference on Computer Vision).

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

TY - GEN

T1 - A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences

AU - Ehrhardt, Jan

AU - Schmidt-Richberg, Alexander

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PY - 2007/12/1

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N2 - In this paper a variational approach for the combined segmentation and registration of temporal image sequences is presented. The purpose of the proposed method is to estimate respiratory-induced organ motion in temporal CT image sequences and to segment a structure of interest simultaneously. In this model the segmentation of all images in the sequences is obtained by finding a non-linear registration to an initial segmentation in a reference image. A dense non-linear displacement field is estimated using image intensities and segmentation information in the images. Both problems (registration and segmentation) are formulated in a joint variational approach and solved simultaneously. A validation of the combined registration and segmentation approach is presented and demonstrates that the simultaneous solution of both problems improves the segmentation performance over a sequential application of the registration and segmentation steps.

AB - In this paper a variational approach for the combined segmentation and registration of temporal image sequences is presented. The purpose of the proposed method is to estimate respiratory-induced organ motion in temporal CT image sequences and to segment a structure of interest simultaneously. In this model the segmentation of all images in the sequences is obtained by finding a non-linear registration to an initial segmentation in a reference image. A dense non-linear displacement field is estimated using image intensities and segmentation information in the images. Both problems (registration and segmentation) are formulated in a joint variational approach and solved simultaneously. A validation of the combined registration and segmentation approach is presented and demonstrates that the simultaneous solution of both problems improves the segmentation performance over a sequential application of the registration and segmentation steps.

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U2 - 10.1109/ICCV.2007.4409148

DO - 10.1109/ICCV.2007.4409148

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SN - 978-1-4244-1631-8

T3 - Proceedings of the IEEE International Conference on Computer Vision

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BT - 2007 IEEE 11th International Conference on Computer Vision

PB - IEEE

T2 - 2007 IEEE 11th International Conference on Computer Vision

Y2 - 14 October 2007 through 21 October 2007

ER -

A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences

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