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

Jan Ehrhardt, Alexander Schmidt-Richberg, Heinz Handels
ICCV 2007 pp. 1-7
doi:10.1109/ICCV.2007.4409148 /iccv/2007/ehrhardt2007iccv-variational/

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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Cite

Text

Ehrhardt et al. "A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences." IEEE/CVF International Conference on Computer Vision, 2007. doi:10.1109/ICCV.2007.4409148

Markdown

[Ehrhardt et al. "A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences." IEEE/CVF International Conference on Computer Vision, 2007.](https://mlanthology.org/iccv/2007/ehrhardt2007iccv-variational/) doi:10.1109/ICCV.2007.4409148

BibTeX

@inproceedings{ehrhardt2007iccv-variational,
  title     = {{A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences}},
  author    = {Ehrhardt, Jan and Schmidt-Richberg, Alexander and Handels, Heinz},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2007},
  pages     = {1-7},
  doi       = {10.1109/ICCV.2007.4409148},
  url       = {https://mlanthology.org/iccv/2007/ehrhardt2007iccv-variational/}
}