Introduction - Prediction and Classification of Respiratory Motion - page 3

networks, where the reconstruction error can be used to build the distribution
model for each breathing class. The sensitivity, specificity and receiver operating
characteristic (ROC) curve of the proposed irregular breathing pattern detector was
analyzed.
References
1. P.J. Keall, G.S. Mageras, J.M. Balter, R.S. Emery, K.M. Forster, S.B. Jiang, J.M. Kapatoes,
D.A. Low, M.J. Murphy, B.R. Murray, C.R. Ramsey, M.B. Van Herk, S.S. Vedam,
J.W. Wong, E. Yorke, The management of respiratory motion in radiation oncology report of
AAPM Task Group 76. Med. Phys. 33(10), 3874-3900 (2006)
2. R.I. Berbeco, S. Nishioka, H. Shirato, G.T.Y. Chen, S.B. Jiang, Residual motion of lung
tumours in gated radiotherapy with external respiratory surrogates. Phys. Med. Biol. 50(16),
3655-3667 (2005)
3. Y.D. Mutaf, C.J. Scicutella, D. Michalski, K. Fallon, E.D. Brandner, G. Bednarz, M.S. Huq,
A simulation study of irregular respiratory motion and its dosimetric impact on lung tumors.
Phys. Med. Biol. 56(3), 845-859 (2011)
4. J.R. Wong, L. Grimm, M. Uematsu, R. Oren, C.W. Cheng, S. Merrick, P. Schiff, Image-guided
radiotherapy for prostate cancer by CT-linear accelerator combination: prostate movements
and dosimetric considerations. Int. J. Radiat. Oncol. Biol. Phys. 61(2), 561-569 (2005)
5. M.J. Fitzpatrick, G. Starkschall, J.A. Antolak, J. Fu, H. Shukla, P.J. Keall, P. Klahr, R.
Mohan, Displacement-based binning of time-dependent computed tomography image data
sets. Med. Phys. 33(1), 235-246 (2006)
6. J. Ehrhardt, R. Werner, D. Säring, T. Frenzel, W. Lu, D. Low, H. Handels, An optical flow
based method for improved reconstruction of 4D CT data sets acquired during free breathing.
Med. Phys. 34(2), 711-721 (2007)
7. K.M. Langen, D.T.L. Jones, Organ motion and its management. Int. J. Radiat. Oncol. Biol.
Phys. 50(1), 265-278 (2001)
8. R. Lu, R.J. Radke, L. Hong, C. Chui, J. Xiong, E. Yorke, A. Jackson, Learning the
relationship between patient geometry and beam intensity in breast intensity-modulated
radiotherapy. IEEE Trans. Biomed. Eng. 53(5), 908-920 (2006)
9. Y. Li, J. Lei, A feasible solution to the beam-angle-optimization problem in radiotherapy
planning with a DNA-based genetic algorithm. IEEE Trans. Biomed. Eng. 57(3), 499-508
(2010)
10. E. Chin, K. Otto, Investigation of a novel algorithm for true 4D-VMAT planning with
comparison to tracked, gated and static delivery. Med. Phys. 38(5), 2698-2707 (2011)
11. A.A. Patel, J.A. Wolfgang, A. Niemierko, T.S. Hong, T. Yock, N.C. Choi, Implications of
respiratory motion as measured by four-dimensional computed tomography for radiation
treatment planning of esophageal cancer. Int. J. Radiat. Oncol. Biol. Phys. 74(1), 290-296 (2009)
12. Q.J. Wu, D. Thongphiew, Z. Wang, V. Chankong, F.F. Yin, The impact of respiratory motion
and treatment technique on stereotactic body radiation therapy for liver cancer. Med. Phys.
5(4), 1440-1451 (2008)
13. T. Depuydt, D. Verellen, O. Haas, T. Gevaert, N. Linthout, M. Duchateau, K. Tournel, T.
Reynders, K. Leysen, M. Hoogeman, G. Storme, M. De Ridder, Geometric accuracy of a
novel gimbals based radiation therapy tumor tracking system. Radiother. Oncol. 98(3),
365-372 (2011)
14. Q. Ren, S. Nishioka, H. Shirato, R.I. Berbeco, Adaptive prediction of respiratory motion for
motion compensation radiotherapy. Phys. Med. Biol. 52(22), 6651-6661 (2007)
15. H. Shirato, S. Shimizu, T. Kunieda, K. Kitamura, M. van Herk, K. Kagei, T. Nishioka, S.
Hashimoto, K. Fujita, H. Aoyama, K. Tsuchiya, K. Kudo, K. Miyasaka, Physical aspects of a