No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
A method to estimate the effect of deformable image registration uncertainties on daily dose mapping
1. M. Birkner et al., “Adapting inverse planning to patient and organ geometrical variation: Algorithm and implementation,” Med. Phys. 30, 2822–2831 (2003).
2. P. Zhang, G. D. Hugo, and D. Yan, “Planning study comparison of real-time target tracking and four-dimensional inverse planning for managing patient respiratory motion,” Int. J. Radiat. Oncol., Biol., Phys, 72(4), 1221–1227 (2008).
4. R. Kashani et al., “Objective assessment of deformable image registration in radiotherapy: A multi-institution study,” Med. Phys. 35(12), 5944–5953 (2008).
5. N. K. Saleh-Sayha, E. Weiss, F. J. Salguero, and J. V. Siebers, “A distance to dose difference tool for estimating the required spatial accuracy of a displacement vector field,” Med. Phys. 38(5), 2318–2323 (2011).
7. G. G. Zhang et al., “Dose mapping: Validation in 4D dosimetry with measurements and application in radiotherapy follow-up evaluation,” Comput. Methods Programs Biomed. 90(1), 25–37 (2008).
8. T. C. Huang et al., “Four-dimensional dosimetry validation and study in lung radiotherapy using deformable image registration and Monte Carlo techniques,” Radiat. Oncol. 5(45), (2010).
10. M. Hub, M. L. Kessler, and C. P. Karger, “A stochastic approach to estimate the uncertainty involved in B-spline image registration,” IEEE Trans. Med. Imaging 28(11), 1708–1716 (2009).
11. F. J. Salguero, N. K. Saleh-Sayah, C. Yan, and J. V. Siebers, “Estimation of three-dimensional intrinsic dosimetric uncertainties resulting from using deformable image registration for dose mapping,” Med. Phys. 38(1), 343–353 (2011).
12. C. Vaman, D. Staub, J. Williamson, and M. J. Murphy, “A method to map errors in the deformable registration of 4DCT images,” Med. Phys. 37(11), 5765–5776 (2010).
13. M. J. Murphy, Z. Wei, M. Fatyga, J. Williamson, M. Anscher, T. Wallace, and E. Weiss, “How does CT image noise affect 3D deformable image registration for image-guided radiotherapy planning?,” Med. Phys. 35(3), 1145–1153 (2008).
16. B. W. Silverman, “Density Estimation for Statistics and Data Analysis,” Monographs on Statistics and Applied Probability (Chapman and Hall, London, 1986).
17. D. W. Scott, “Multivariate Density Estimation: Theory, Practice, and Visualization” (John Wiley, New York, 1992).
18. A. W. Bowman and A. Azzalini, Applied Smoothing Techniques for Data Analysis (Oxford University Press, London, 1997).
19. C. M. Bishop, Pattern Recognition and Machine Learning (Springer, New York, 2006).
Article metrics loading...
Full text loading...
Most read this month