Abstract
Detailed analysis of breathing dynamics, as motivated by radiotherapy of lung tumors, requires accurate estimates of inner lung motion fields. We present an evaluation and comparison study of non-linear non-parametric intensity-based registration approaches to estimate these motion fields in 4D CT images. In order to cope with discontinuities in pleura and chest wall motion we restrict the registration by applying lung segmentation masks and evaluate the impact of masking on registration accuracy. Furthermore, we compare diffusive to elastic regularization and diffeomorphic to non-diffeomorphic implementations. Based on a data set of 10 patients we show that masking improves registration accuracy significantly. Moreover, neither elastic or diffusive regularization nor diffeomorphic versus non-diffeomorphic implementation influence the accuracy significantly. Thus, the method of choice depends on the application and requirements on motion field characteristics.
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References
Li XA, et al. Point/counterpoint: Respiratory gating for radiation therapy is not ready for prime time. Med Phys. 2007;34(3):867–70.
Sarrut D, et al. A comparison framework for breathing motion estimation methods from 4-D imaging. IEEE Trans Med Imaging. 2007;26(12):1636–48.
Vik T, et al. Validation and comparison of registration methods for free-breathing 4D lung-CT. Procs SPIE. 2008;6914:2Pl–10.
Werner R, et al. Validation and comparison of a biophysical modeling approach and non-linear registration for estimation of lung motion fields in thoracic 4D CT data. Procs SPIE. 2009.
Modersitzki J. Numerical Methods for Image Registration. Oxford University Press; 2003.
Vercauteren T, et al. Symmetric log-domain diffeomorphic registration: A demons-based approach. Procs MICCAI. 2008.
Ehrhardt J, et al. Generation of a mean motion model of the lung using 4D-CT image data. Procs VCBM. 2008; p. 69–76.
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© 2009 Springer-Verlag Berlin Heidelberg
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Werner, R., Ehrhardt, J., Schmidt-Richberg, A., Cremers, F., Handels, H. (2009). Estimation of Inner Lung Motion Fields by Non-linear Registration. In: Meinzer, HP., Deserno, T.M., Handels, H., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2009. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93860-6_21
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DOI: https://doi.org/10.1007/978-3-540-93860-6_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-93859-0
Online ISBN: 978-3-540-93860-6
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