Temporal groupwise registration for motion modeling

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6801 LNCS, Issue , 2011, Pages 648-659

  Yigitsoy, Mehmet ^a   Wachinger, Christian ^a   Navab, Nassir ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DEFORMATION FIELD; FREE-FORM DEFORMATION; GROUPWISE NON-RIGID REGISTRATION; IMAGING ARTIFACTS; MEDICAL DATA; MEDICAL IMAGES; MOTION MODELING; NON-RIGID MOTION; NOVEL METHODS; REGISTRATION METHODS; SPATIO-TEMPORAL; SPATIO-TEMPORAL REGISTRATION; TEMPORAL INFORMATION; TIME-RESOLVED IMAGE;

DATA PROCESSING; DEFORMATION; STORMS;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; MOVEMENT (PHYSIOLOGY); REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, BIOLOGICAL; MOVEMENT; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 80052340499     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-22092-0_53     Document Type: Conference Paper

References (30)

1. Bai, W., Brady, S.: Spatio-temporal image registration for respiratory motion correction in pet imaging. In: ISBI, pp. 426-429. IEEE, Los Alamitos (2009)
2. Balci, S., Golland, P.,Wells,W.: Non-rigid Groupwise Registration using B-Spline Deformation Model. In: Workshop on Open-Source and Open-Data for 10th MICCAI, pp. 105-121. Citeseer (2007)
3. Bystrov, D., Vik, T., Schulz, H., Klinder, T., Schmidt, S.: Local motion analysis in 4D lung CT using fast groupwise registration. In: Proceedings of the 16th IEEE International Conference on Image Processing, pp. 1729-1732. IEEE Press, Los Alamitos (2009)
4. Castillo, E., Castillo, R., Martinez, J., Shenoy, M., Guerrero, T.: Four-dimensional deformable image registration using trajectory modeling. PMB 55, 305 (2010)
5. Colgan, R., McClelland, J., McQuaid, D., Evans, P., Hawkes, D., Brock, J., Landau, D., Webb, S.: Planning lung radiotherapy using 4D CT data and a motion model. Physics in Medicine and Biology 53, 5815 (2008)
6. Crum, W., Hartkens, T., Hill, D.: Non-rigid image registration: theory and practice. British Journal of Radiology 77(Special Issue 2), S140 (2004)
7. Ehrhardt, J.,Werner, R., Frenzel, T., Säring, D., Lu,W., Low, D., Handels, H.: Reconstruction of 4D-CT data sets acquired during free breathing for the analysis of respiratory motion. In: Proc. of SPIE, vol. 6144, pp. 365-372 (2006)
8. Flampouri, S., Jiang, S., Sharp, G., Wolfgang, J., Patel, A., Choi, N.: Estimation of the delivered patient dose in lung IMRT treatment based on deformable registration of 4D-CT data and Monte Carlo simulations. Physics in Medicine and Biology 51, 2763 (2006)
9. Joshi, S., Davis, B., Jomier, M., Gerig, G.: Unbiased diffeomorphic atlas construction for computational anatomy. NeuroImage 23, 151-160 (2004)
10. King, A., Buerger, C., Schaeffter, T.: Cardiac Respiratory Motion Modelling by Simultaneous Registration and Modelling from Dynamic MRI Images. In: WBIR, pp. 222-233 (2010)
11. Klein, G., Huesman, R.: Four-dimensional processing of deformable cardiac PET data. Medical Image Analysis 6(1), 29-46 (2002)
12. Learned-Miller, E.G.: Data driven image models through continuous joint alignment. IEEE Trans on Pattern Analysis and Machine Intelligence 28(2), 236-250 (2006)
13. Ledesma-Carbayo, M., Kybic, J., Desco, M., Santos, A., Sühling, M., Hunziker, P., Unser, M.: Spatio-temporal nonrigid registration for ultrasound cardiac motion estimation. IEEE Transactions on Medical Imaging 24(9), 1113 (2005)
14. McClelland, J., Blackall, J., Tarte, S., Chandler, A., Hughes, S., Ahmad, S., Landau, D., Hawkes, D.: A continuous 4D motion model from multiple respiratory cycles for use in lung radiotherapy. Medical Physics 33, 3348 (2006)
15. Perperidis, D., Mohiaddin, R., Rueckert, D.: Spatio-temporal free-form registration of cardiac MR image sequences. Medical Image Analysis 9(5), 441-456 (2005)
16. Peyrat, J., Delingette, H., Sermesant, M., Xu, C., Ayache, N.: Registration of 4D Cardiac CT Sequences Under Trajectory Constraints With Multichannel Diffeomorphic Demons. IEEE T-MI (2010)
17. Rohlfing, T., Maurer Jr., C., O'Dell, W., Zhong, J.: Modeling liver motion and deformation during the respiratory cycle using intensity-based nonrigid registration of gated MR images. Medical Physics 31, 427 (2004)
18. Rueckert, D., Aljabar, P.,Heckemann, R.A., Hajnal, J.V., Hammers, A.: Diffeomorphic registration using B-splines. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4191, pp. 702-709. Springer, Heidelberg (2006)
19. Rueckert, D., Sonoda, L., Hayes, C., Hill, D., Leach, M., Hawkes, D.: Nonrigid registration using free-form deformations: application to breast MR images. IEEE Transactions on Medical Imaging 18(8) (1999)
20. Sarrut, D., Boldea, V., Miguet, S., Ginestet, C.: Simulation of four-dimensional CT images from deformable registration between inhale and exhale breath-hold CT scans. Medical Physics 33, 605 (2006)
21. Schreibmann, E., Chen, G., Xing, L.: Image interpolation in 4D CT using a BSpline deformable registration model. IJROBP 64(5), 1537-1550 (2006)
22. Sundar, H., Litt, H., Shen, D.: Estimating myocardial motion by 4D image warping. Pattern Recognition 42(11), 2514-2526 (2009)
23. Vandemeulebroucke, J., Sarrut, D., Clarysse, P.: The popi-model, a point-validated pixel-based breathing thorax model. In: ICCR, Toronto, Canada (2007)
24. Vercauteren, T., Pennec, X., Perchant, A., Ayache, N.: Diffeomorphic demons using ITK's finite difference solver hierarchy. The Insight Journal (2008)
25. Viola, P., Wells III, W.: Alignment by maximization of mutual information. International Journal of Computer Vision 24(2), 137-154 (1997)
26. Von Siebenthal, M., Szekely, G., Gamper, U., Boesiger, P., Lomax, A., Cattin, P.: 4D MR imaging of respiratory organ motion and its variability. PMB 52, 1547 (2007)
27. Wachinger, C., Navab, N.: Similarity Metrics and Efficient Optimization for Simultaneous Registration. In: CVPR (2009)
28. Wachinger, C., Yigitsoy, M., Navab, N.: Manifold learning for image-based breathing gating with application to 4D ultrasound. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010. LNCS, vol. 6362, pp. 26-33. Springer, Heidelberg (2010)
29. Wu, G., Wang, Q., Jia, H., Shen, D.: Registration of longitudinal image sequences with implicit template and spatial-temporal heuristics. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010. LNCS, vol. 6362, pp. 618-625. Springer, Heidelberg (2010)
30. Zöllei, L., Learned-Miller, E., Grimson, E.,Wells,W.: Efficient population registration of 3D data. In: Computer Vision for Biomedical Image Applications, pp. 291-301 (2005)