Statistical modeling of 4D respiratory lung motion using diffeomorphic image registration

IEEE Transactions on Medical Imaging

Volumn 30, Issue 2, 2011, Pages 251-265

  Ehrhardt, Jan ^a   Werner, René ^a   Schmidt Richberg, Alexander ^a   Handels, Heinz ^a  

^a UNIVERSITY OF LÜBECK   (Germany)

Author keywords

4D computed tomography (CT); Diffeomorphic registration; motion modeling; respiratory motion; statistical atlas generation

Indexed keywords

COMPUTED TOMOGRAPHY; DIFFEOMORPHIC REGISTRATION; MOTION MODELING; RESPIRATORY MOTIONS; STATISTICAL ATLAS GENERATION;

BIOLOGICAL ORGANS; DISEASES; FORECASTING; IMAGE REGISTRATION; MEDICAL IMAGING; RADIOTHERAPY; RESPIRATORY MECHANICS; STATISTICS; THREE DIMENSIONAL; TUMORS;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; FOUR DIMENSIONAL COMPUTED TOMOGRAPHY; HUMAN; IMAGE PROCESSING; LUNG; METHODOLOGY; MOVEMENT (PHYSIOLOGY); RADIOGRAPHY; STATISTICAL MODEL;

ALGORITHMS; FOUR-DIMENSIONAL COMPUTED TOMOGRAPHY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LUNG; MODELS, BIOLOGICAL; MODELS, STATISTICAL; MOVEMENT;

EID: 79551612663     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2010.2076299     Document Type: Article

References (54)

1. P. J. Keall et al., "The management of respiratory motion in radiation oncology report of AAPM task group 76," Med. Phys., vol. 33, no. 10, pp. 3874-3900, 2006.
2. E. C. Ford, G. S. Mageras, E. Yorke, and C. C. Ling, " Respirationcorre-lated spiral CT: A method of measuring respiratory-induced anatomic motion for radiation treatment planning," Med. Phys., vol. 30, no. 1, pp. 88-97, 2003.
3. P. J. Keall, S. Joshi, S. S. Vedam, J. V. Siebers, V. R. Kini, and R. Mohan, "Four-dimensional radiotherapy planning for DMLC-based respiratory motion tracking," Med. Phys., vol. 32, no. 4, pp. 942-951, 2005.
4. T. Guerrero, K. Sanders, E. Castillo, Y. Zhang, L. Bidaut, T. Pan, and R. Komaki, "Dynamic ventilation imaging from four-dimensional computed tomography.," Phys. Med. Biol., vol. 51, no. 4, pp. 777-791, 2006.
5. J. M. Reinhardt, K. Ding, K. Cao, G. E. Christensen, E. A. Hoffman, and S. V. Bodas, "Registration-based estimates of local lung tissue expansion compared to Xenon CT measures of specific ventilation.," Med. Image Anal., vol. 12, no. 6, pp. 752-763, 2008.
6. D.Sarrut, V. Boldea, S. Miguet, and C. Ginestet, "Simulationof fourdi-mensional CT images from deformable registration between inhale and exhale breath-hold CT scans," Med. Phys., vol. 33, no. 3, pp. 605-617, 2006.
7. S. A. Nehmeh, Y. E. Erdi, T. Pan, E. Yorke, G. S. Mageras, K. E. Rosenzweig, H. Schoder, H. Mostafavi, O. Squire, A. Pevsner, S. M. Larson, and J. L. Humm, "Quantitation of respiratory motion during 4D-PET/CT acquisition.," Med. Phys., vol. 31, no. 6, pp. 1333-1338, 2004.
8. S. S. Vedam, P. J. Keall, A. Docef, D. A. Todor, V. R. Kini, and R. Mohan, "Predicting respiratory motion for four-dimensional radiotherapy.," Med. Phys., vol. 31, no. 8, pp. 2274-2283, 2004.
9. J.M.Blackall,S.Ahmad,M.E.Miquel,J.R.McClelland,D.B.Landau, and D. J. Hawkes, "MRI-based measurements of respiratory motion variability and assessment of imaging strategies for radiotherapy planning.," Phys. Med. Biol., vol. 51, no. 17, pp. 4147-4169, 2006.
10. D. A. Low, P. J. Parikh, W. Lu, J. F. Dempsey, S. H. Wahab, J. P. Hubenschmidt, M. M. Nystrom, M. Handoko, and J. D. Bradley, "Novel breathing motion model for radiotherapy.," Int. J. Radiat. Oncol. Biol. Phys., vol. 63, no. 3, pp. 921-929, 2005.
11. J. R. McClelland, J. M. Blackall, S. Tarte, A. C. Chandler, S. Hughes, S. Ahmad, D. B. Landau, and D. J. Hawkes, "A continuous 4D motion model from multiple respiratory cycles for use in lung radiotherapy," Med. Phys., vol. 33, no. 9, pp. 3348-3358, 2006.
12. C. Coolens, S. Webb, H. Shirato, K. Nishioka, and P. M. Evans, "A margin model to account for respiration-induced tumour motion and its variability.," Phys. Med. Biol., vol. 53, no. 16, pp. 4317-4330, 2008.
13. T. Neicu,H. Shirato, Y.Seppenwoolde, and S. B. Jiang, "Synchronized moving aperture radiation therapy (SMART): Average tumour trajectory for lung patients.," Phys. Med. Biol., vol. 48, no. 5, pp. 587-598, 2003.
14. R. Chandrashekara, A. Rao, G. Sanchez-Ortiz, R. Mohiaddin, and D. Rueckert, "Construction of a statistical model for cardiac motion analysis using nonrigid image registration," in Proc. Information Processing in Medical Imaging, ser. Lecture Notes in Computer Science, G. Goos, J. Hartmanis, and J. van Leeuwen, Eds. New York: Springer, 2003, vol. 2732, pp. 599-610.
15. D. Perperidis, R. Mohiaddin, and D. Rueckert, "Construction of a 4D statistical atlas of the cardiac anatomy and its use in classification," in Proc. Med. Image Computing and Computer-Assisted Intervent. (MICCAI 2005), ser. Lecture Notes in Computer Science, J. S. Duncan andG.Gerig, Eds. New York: Springer, 2005, vol. 3750, pp. 402-410.
16. A. Rao, R. Chandrashekara, G. Sanchez-Ortiz, R. Mohiaddin, P. Aljabar, J. Hajnal, B. Puri, and D. Rueckert, "Spatial transformation of motion and deformation fields using nonrigid registration," IEEE Trans. Med. Imag., vol. 23, no. 9, pp. 1065-1076, Sep. 2004.
17. T. A. Sundaram, B. B. Avants, and J. C. Gee, "A dynamic model of average lung deformation using capacity-based reparameterization and shape averaging of lung mr images," in Proc. Med. Image Computing and Computer-Assisted Intervent. (MICCAI 2004), ser. Lecture Notes in Computer Science, C. Barillot, D. R. Haynor, and P. Hellier, Eds. New York: Springer, 2004, vol. 3217, pp. 1000-1007.
18. V. Arsigny, "Processing data in lie groups: An algebraic approach. application to non-linear registration and diffusion tensor MRI" Ph.D. dissertation, École Polytechnique, Palaiseau, France, Nov. 2006 [Online]. Available: http://wwwsop.inria.fr/asclepios/Publications/Ar-signy/arsigny phd.pdf
19. T. Vercauteren, X. Pennec, A. Perchant, and N. Ayache, "Diffeo-morphic demons: Efficient non-parametric image registration.," Neuroimage, vol. 45, no. 1, pp. S61-S72, 2008.
20. V. Arsigny, O. Commowick, X. Pennec, and N. Ayache, "A log- Euclidean framework for statistics on diffeomorphisms," in Proc. Med. Image Computing and Computer-Assisted Intervent. (MICCAI 2006), ser. Lecture Notes in Computer Science, R. Larsen, M. Nielsen, and J. Sporring, Eds. New York: Springer, Oct. 2-4, 2006, vol. 4190, pp. 924-931.
21. M. F. Beg, M. I. Miller, A. Trouve, and L. Younes, "Computing large deformation metric mappings via geodesic flows of diffeomorphisms," Int. J. Comp. Vis., vol. 61, no. 2, pp. 139-157, 2005.
22. X. Pennec, "Intrinsic statistics on riemannian manifolds: Basic tools for geometric measurements," J. Math. Imag. Vis., vol. 25, no. 1, pp. 127-154, 2006.
23. D. A. Low, M. Nystrom, E. Kalinin, P. Parikh, J. F. Dempsey, J. D. Bradley, S. Mutic, S. H. Wahab, T. Islam, G. Christensen, D. G. Politte, and B. R. Whiting, "A method for the reconstruction of four-dimensional synchronized ct scans acquired during free breathing," Med. Phys., vol. 30, no. 6, pp. 1254-1263, 2003.
24. W. Lu, P. J. Parikh, I. M. El Naqa, M. M. Nystrom, J. P. Hubenschmidt, S. H. Wahab, S. Mutic, A. K. Singh, G. E. Christensen, J. D. Bradley, and D. A. Low, "Quantitation of the reconstruction quality of a four-dimensional computed tomography process for lung cancer patients," Med. Phys., vol. 32, pp. 890-901, 2005.
25. J. Ehrhardt, R. Werner, D. Säring, T. Frenzel, W. Lu, D. Low, and H. Handels, "An optical flow based method for improved reconstruction of 4D CT data sets acquired during free breathing.," Med. Phys., vol. 34, no. 2, pp. 711-721, 2007.
26. J. Ehrhardt, D. Säring, and H. Handels, "Structure-preserving interpolation of temporal and spatial image sequences using an optical flow based method," Methods Inf. Med., vol. 46, pp. 300-307, 2007.
27. J.-M. Peyrat, H. Delingette, M. Sermesant, X. Pennec, C. Xu, and N. Ayache, "Registration of 4D time-series of cardiac images with multichannel diffeomorphic demons," in Proc. Med. Image Computing and Computer-Assisted Intervent. (MICCAI 2008), ser. Lecture Notes in Computer Science, D. N. Metaxas, L. Axel, G. Fichtinger, and G. Székely, Eds. New York: Springer, 2008, vol. 5241, pp. 972-979.
28. A. Trouve, "Diffeomorphisms groups and pattern matching in image analysis," Int. J. Comp. Vis., vol. 28, no. 3, pp. 213-221, 1998.
29. J. Ashburner, "A fast diffeomorphic image registration algorithm.," Neuroimage, vol. 38, no. 1, pp. 95-113, 2007.
30. M. Hernandez, M. N. Bossa, and S. Olmos, "Registrationof anatomical images using paths of diffeomorphisms parameterized with stationary vector field flows," Int. J. Comp. Vis., vol. 85, pp. 291-306, 2009.
31. S. Marsland and C. J. Twining, "Constructing an atlas for the diffeo-morphism group of a compact manifold with boundary, with application to the analysis of image registrations," J. Comput. Appl. Math., vol. 222, no. 2, pp. 411-428, 2008.
32. T. Vercauteren, X. Pennec, A. Perchant, and N. Ayache, "Symmetric logdomain diffeomorphic registration: A demons-based approach," in Proc. Med. Image Computing and Computer-Assisted Intervent. (MICCAI 2008), ser. Lecture Notes in Computer Science, D. N. Metaxas, L. Axel, G. Fichtinger, and G. Székely, Eds. New York: Springer, 2008, vol. 5241, pp. 754-761.
33. J. Modersitzki, Numerical Methods for Image Registration. New York: Oxford Univ. Press, 2003.
34. J.-P. Thirion, "Image matching as a diffusion process: An analogy with Maxwell's demons,"Med. Image Anal., vol.2,no.3,pp.243-260, 1998.
35. P. Cachier, E. Bardinet, D. Dormont, X. Pennec, and N. Ayache, "Iconic feature based nonrigid registration: The pasha algorithm," Comput. Vis. Image Understand., vol. 89, no. 2-3, pp. 272-298, 2003.
36. J. Weickert, B. M. T. H. Romeny, and M. A. Viergever, "Efficient and reliable schemes for nonlinear diffusion filtering," IEEE Trans. Image Process., vol. 7, no. 3, pp. 398-410, Mar. 1998.
37. A. Guimond, J. Meunier, and J.-P. Thirion, "Average brain models: A convergence study," Comput. Vis. Image Understand., vol. 77, no. 2, pp. 192-210, 2000.
38. S. Joshi, B. Davis, M. Jomier, and G. Gerig, "Unbiased diffeomorphic atlas construction for computational anatomy.," Neuroimage, vol. 23, pp. S151-S160, 2004.
39. D.Rueckert,A.Frangi, andJ.Schnabel, "Automatic constructionof3D statistical deformation models of the brain using nonrigid registration," IEEE Trans. Med. Imag., vol. 22, no. 8, pp. 1014-1025, Aug. 2003.
40. M. Vaillant, M. I. Miller, L. Younes, and A. Trouve, "Statistics on dif-feomorphisms via tangent space representations.," Neuroimage, vol. 23, pp. S161-S169, 2004.
41. M. I. Miller and L. Younes, "Group actions, homeomorphisms, and matching: A general framework," Int. J. Comp. Vis., vol. 41, no. 1-2, pp. 61-84, 2001.
42. V. Arsigny, P. Fillard, X. Pennec, and N. Ayache, "Geometric means in a novel vector space structure on symmetric positive-definite matrices," SIAM J. Matrix Anal. Appl., vol. 29, no. 1, pp. 328-347, 2007.
43. M. N. Bossa and S. O. Gasso, "A new algorithm for the computation of the group logarithm of diffeomorphisms," in Proc. Int. Workshop Math. Foundations Computat. Anatomy (MFCA 2008), X. Pennec and S. Joshi, Eds., New York, 2008, pp. 13-23.
44. S. Hu, E. Hoffman, and J. Reinhardt, "Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images," IEEE Trans. Med. Imag., vol. 20, no. 6, pp. 490-498, Jun. 2001.
45. B. Avants and J. C. Gee, "Geodesic estimation for large deformation anatomical shape averaging and interpolation.," Neuroimage, vol. 23, pp. S139-S150, 2004.
46. R. Werner, J. Ehrhardt, T. Frenzel, D. Säring, W. Lu, D. Low, and H. Handels, "Motion artifact reducing reconstruction of 4D CTimage data for the analysis of respiratory dynamics.," Methods Inf. Med., vol. 46, no. 3, pp. 254-260, 2007.
47. Y. Yin, E. A. Hoffman, and C.-L. Lin, "Mass preserving nonrigid registration of CT lung images using cubic B-spline," Med. Phys., vol. 36, no. 9, pp. 4213-4222, 2009.
48. P. J. Besl and N. D. McKay, "A method for registration of 3-D shapes," IEEE Trans. Pattern Anal. Mach. Intell., vol. 14, no. 2, pp. 239-256, Feb. 1992.
49. C. Plathow, C. Fink, S. Ley, M. Puderbach, M. Eichinger, I. Zuna, A. Schmähl, and H. Kauczor, "Measurement of tumor diameter-dependent mobility of lung tumors by dynamic MRI.," Radiother. Oncol., vol. 73, pp. 349-354, 2004. (Pubitemid 39601084)
50. ICRU, Report 62: Prescribing, Recording and Reporting Photon Beam Therapy (Supplement to ICRU Report 50) Int. Commision Radiation Units Measurements, Tech. Rep., 1999.
51. R. Kashani, M. Hub, J. M. Balter, M. L. Kessler, L. Dong, L. Zhang, L. Xing, Y. Xie, D. Hawkes, J. A. Schnabel, J. McClelland, S. Joshi, Q. Chen, and W. Lu, "Objective assessment of deformable image registration in radiotherapy: A multi-institution study," Med. Phys., vol. 35, no. 12, pp. 5944-5953, 2008.
52. R. Castillo, E. Castillo, R. Guerra, V. E. Johnson, T. McPhail, A. K. Garg, and T. Guerrero, "A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets," Phys. Med. Biol., vol. 54, no. 7, pp. 1849-1870, 2009.
53. R. Werner, J. Ehrhardt, R. Schmidt, and H. Handels, "Patient- specific finite element modeling of respiratory lung motion using 4D CT image data.," Med. Phys., vol. 35, no. 5, pp. 1500-1511, 2009.
54. J. Ehrhardt, R. Werner, A. Schmidt-Richberg, and H. Handels, "A statistical shape and motion model for the prediction of respiratory lung motion," in Medical Imaging 2010: Image Processing, B. M. Dawant and D. R. Haynor, Eds. Bellingham, WA: SPIE, 2010, vol. 7623, p. 762353.