Combining a breathing model and tumor-specific rigidity constraints for registration of CT-PET thoracic data

References

• Lavely W, Scarfone C, Cevikalp H, Li R, Byrne D, Cmelak A, Dawant B, Price R, Hallahan D, Fitzpatrick J. Phantom validation of coregistration of PET and CT for image-guided radiotherapy. Med Phys 2004; 31(5)1083–1092
   PubMed Web of Science ®Google Scholar
• Rizzo G, Castiglioni I, Arienti R, Cattaneo G, Landoni C, Artioli D, Gilardi M, Messa C, Reni M, Ceresoli G, et al. Automatic registration of PET and CT studies for clinical use in thoracic and abdominal conformal radiotherapy. Phys Med Biol 2005; 49(3)267–279
   Google Scholar
• Vogel W, van Dalen J, Schinagl D, Kaanders J, Huisman H, Corstens F, Oyen W. Correction of an image size difference between positron emission tomography (PET) and computed tomography (CT) improves image fusion of dedicated PET and CT. Phys Med Biol 2006; 27(6)515–519
   Google Scholar
• Townsend D, Carney J, Yap J, Hall N. PET/CT today and tomorrow. J Nuclear Med 2004; 45(1 Suppl.)4–14
   Google Scholar
• Shekhar R, Walimbe V, Raja S, Zagrodsky V, Kanvinde M, Wu G, Bybel B. Automated 3-dimensional elastic registration of whole-body PET and CT from separate or combined scanners. J Nuclear Med 2005; 46(9)1488–1496
   PubMed Web of Science ®Google Scholar
• Kybic J, Unser M. Fast parametric elastic image registration. IEEE Trans Image Processing 2003; 12(11)1427–1442
   PubMed Web of Science ®Google Scholar
• D'Agostino E, Maes F, Vandermeulen D, Suetens P. A viscous fluid model for multimodal nonrigid image registration using mutual information. Med Image Anal 2003; 7(4)565–575
   PubMed Web of Science ®Google Scholar
• Thirion JP. Image matching as a diffusion process: An analogy with Maxwell's demons. Med Image Anal 1998; 2(3)243–260
   PubMedGoogle Scholar
• Zitovà B, Flusser J. Image registration methods: A survey. Image and Vision Computing 2003; 21: 977–1000
   Web of Science ®Google Scholar
• Maintz J, Viergever M. A survey of medical image registration. Med Image Anal 1998; 2(1)1–36
   PubMedGoogle Scholar
• Pluim J, Fitzpatrick J. Image registration. IEEE Trans Med Imaging 2003; 22(11)1341–1343
   PubMed Web of Science ®Google Scholar
• Rohlfing T, Maurer C, Bluemke D, Jacobs M. Volume-preserving nonrigid registration of MR breast images using free-form deformation with an incompressibility constraint. IEEE Trans Med Imaging 2003; 22(6)730–741
   PubMed Web of Science ®Google Scholar
• Xiaohua C, Brady M, Lo JLC, Moore N. Simultaneous segmentation and registration of contrast-enhanced breast MRI. Proceedings of the International Conference on Information Processing in Medical Imaging (IPMI 2005), Glenwood Springs, CO, July 2005. Springer, Lecture Notes in Computer Science 3565. Berlin 2005; 126–137
   Google Scholar
• Hartkens T, Hill D, Castellano-Smith A, Hawkes D, Maurer C, Jr, Martin A, Hall W, Liu H, Truwit C. Using points and surfaces to improve voxel-based non-rigid registration. Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2002), Tokyo, Japan, September 2002. Part II, T Dohi, R Kikinis. Springer, Lecture Notes in Computer Science 2489. Berlin 2002; 565–572
   Google Scholar
• West JB, Maurer C, Jr, Dooley JR. Hybrid point-andintensity-based deformable registration for abdominal CT images. Proceedings of the SPIE Medical Imaging 2005: Image Processing, JM Fitzpatrick, JM Reinhardt, 2005; 5747: 204–211, Proceedings of the SPIE
   Google Scholar
• Little JA, Hill DLG, Hawkes DJ. Deformations incorporating rigid structures. Computer Vision and Image Understanding 1997; 66(2)223–232
   Web of Science ®Google Scholar
• Moreno A, Chambon S, Santhanam A, Rolland J, Angelini E, Bloch I. Thoracic CT-PET registration using a 3D breathing model. Proceedings of the 10th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2007), Brisbane, Australia, 29 October-2 November 2007, N Ayache, S Ourselin, AJ Maeder. Springer, Berlin 2007; 626–633, Part I. Lecture Notes in Computer Science 4791
   Google Scholar
• Sarrut D. Deformable registration for image-guided radiation therapy. Zeitschrift für Medizinische Physik 2006; 13: 285–297
   Google Scholar
• Crawford C, King K, Ritchie C, Godwin J. Respiratory compensation in projection imaging using a magnification and displacement model. IEEE Trans Med Imaging 1996; 15(3)327–332
   PubMed Web of Science ®Google Scholar
• Wolthaus J, van Herk M, Muller S, Belderbos J, Lebesque J, de Bois J, Rossi M, Damen E. Fusion of respiration-correlated PET and CT scans: Correlated lung tumour motion in anatomical and functional scans. Phys Med Biol 2005; 50(7)1569–1583
   PubMed Web of Science ®Google Scholar
• Zhang T, Keller H, Jeraj R, Manon R, Welsh J, Patel R, Fenwick J, Mehta M, Mackie T. Breathing synchronized delivery - a new technique for radiation treatment of the targets with respiratory motion. Int J Radiat Oncol Biol Phys 2003; 57(2)185–186
   Google Scholar
• Nehmeh S, Erdi Y, Pan T, Pevsner A, Rosenzweig K, Yorke E, Mageras G, Schoder H, Vernon P, Squire O, Mostafavi H, Larson S, Humm J. Four-dimensional (4D) PET/CT imaging of the thorax. Phys Med Biol 2004; 31(12)3179–3186
   Google Scholar
• Schweikard A, Glosser G, Bodduluri M, Murphy M, Adler J. Robotic motion compensation for respiratory movement during radiosurgery. Comput Aided Surg 2000; 5(4)263–277
   PubMedGoogle Scholar
• 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. Med Phys 2006; 33(9)3348–3358
   PubMed Web of Science ®Google Scholar
• Neicu T, Shirato H, Seppenwoolde Y, Jiang S. Synchronized Moving Aperture Radiation Therapy SMART): average tumour trajectory for lung patients. Phys Med Biol 2003, 48: 587–598
   PubMedGoogle Scholar
• Rohlfing T, Maurer C, Zhong J. Modeling liver motion and deformation during the respiratory cycle using intensity-based free-form registration of gated MR images. Proceedings of SPIE Medical Imaging 2001: Visualization, Display, and Image-Guided. Proceedings of the SPIE 2001; 4319: 337–348
   Google Scholar
• Sarrut D, Boldea V, Ayadi M, Badel J, Ginestet C, Clippe S, Carrie C. Non-rigid registration method to assess reproducibility of breath-holding with ABC in lung cancer. Int J Radiat Oncol Biol Phys 2005; 61(2)594–607
   PubMed Web of Science ®Google Scholar
• Segars W, Lalush D, Tsui B. Study of the efficacy of respiratory gating in myocardial SPECT using the new 4-D NCAT phantom. IEEE Trans Nuclear Sci 2002; 49(3)675–679
   Web of Science ®Google Scholar
• Rohlfing T, Maurer C, Zhong J. Modeling liver motion and deformation during the respiratory cycle using intensity-based free-form registration of gated MR images. Med Phys 2004; 31(3)427–432
   PubMed Web of Science ®Google Scholar
• Guerrero T, Kamel E, Seifert B, Burger C, Buck A, Hany T, von Schulthess G. Elastic image mapping for 4-D dose estimation in thoracic radiotherapy. Radiation Protection Dosimetry 2005; 115(1-4)497–502
   PubMed Web of Science ®Google Scholar
• Zordan V, Celly B, Chiu B, DiLorenzo P. Breathe easy: Model and control of human respiration for computer animation. Graphical Models 2006; 68(2)113–132
   Web of Science ®Google Scholar
• Santhanam A, Imielinska C, Davenport P, Kupelian P, Rolland J. Modeling and simulation of real-time 3D lung dynamics. IEEE Trans Information Technol Biomed 2008; 12(2)257–270
   PubMedGoogle Scholar
• Narusawa U. General characteristics of the sigmoidal model equation representing quasistatic pulmonary P-V curves. J Applied Physiol 2001; 92(1)201–210
   Google Scholar
• Venegas J, Harris R, Simon B. A comprehensive equation for the pulmonary pressure volume curve. J Applied Physiol 1998; 84(1)389–395
   PubMed Web of Science ®Google Scholar
• Promayon E, Baconnier P, Puech C. Physically-based model for simulating the human trunk respiration movements. Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery (CVRMed-MRCAS ’97), Grenoble, France, March, 1997, J Troccaz, E Grimson, R Mösges. Springer, Lecture Notes in Computer Science 1205. Berlin, 1997. pp 379–388.
   Google Scholar
• Pollari M, Lotjonen J, Makela T, Pauna N, Reilhac A, Clarysse P. Evaluation of cardiac PET-MRI registration methods using a numerical breathing phantom. Proceedings of the IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2004), Arlington, VA, April, 2004, 1447–1450.
   Google Scholar
• Sundaram T, Gee J. Towards a model of lung biomechanics: Pulmonary kinematics via registration of serial lung images. Med Image Anal 2005; 9(6)524–537
   Google Scholar
• Ehrhardt J, Schmidt-Richberg A, Handels H. A variational approach for combined segmentation and estimation of respiratory motion in temporal image sequences. Proceedings of the 11th IEEE International Conference on Computer Vision (ICCV 2007), Rio de Janeiro, Brazil, October, 2007
   Google Scholar
• Camara O, Delso G, Colliot O, Moreno-Ingelmo A, Bloch I. Explicit incorporation of prior anatomical information into a nonrigid registration of thoracic and abdominal CT and 18-FDG whole-body emission PET images. IEEE Trans Med Imaging 2007; 26(2)164–178
   PubMed Web of Science ®Google Scholar
• Moreno A. Non-linear registration of thoracic PET and CT images for the characterization of tumors: Application to radiotherapy. PhD thesis, Ecole Nationale Supérieure des Télécommunications,. Paris, France 2007
   Google Scholar
• Moreno A, Takemura C, Colliot O, Camara O, Bloch I. Using anatomical knowledge expressed as fuzzy constraints to segment the heart in CT images. Pattern Recognition 2008; 41(8)2525–2540
   Web of Science ®Google Scholar
• Bloch I, Colliot O, Cesar R. On the ternary spatial relation “between”. IEEE Trans Systems, Man, and Cybernetics SMC-B 2006; 36(2)312–327
   PubMed Web of Science ®Google Scholar
• Santhanam A. Modeling, simulation, and visualization of 3D lung dynamics. PhD thesis. University of Central Florida, Orlando, FL 2006
   Google Scholar
• Beil W, Rohr K, Stiehl HS (1997) Investigation of approaches for the localization of anatomical landmarks in 3D medical images. Computer Assisted Radiology and Surgery. Proceedings of the 11th International Symposium and Exhibition (CAR’ 97), Berlin, June, 1997, HU Lemke, MW Vannier, K Inamura. Elsevier, Amsterdam, 265–270.
   Google Scholar
• Rohr K, Stiehl H, Sprengel R, Buzug T, Weese J, Kuhn M. Landmark-based elastic registration using approximating thin-plate splines. IEEE Trans Med Imaging 2001; 20(6)526–534
   PubMed Web of Science ®Google Scholar
• Betke M, Hong H, Thomasa D, Princea C, Kob J. Landmark detection in the chest and registration of lung surfaces with an application to nodule registration. Med Image Anal 2003; 7(3)265–281
   PubMed Web of Science ®Google Scholar
• Bajcsy R, Kovačič S. Distance transformations in digital images. Computer Vision, Graphics, and Image Processing (CVGIP) 1986; 34(3)344–371
   Web of Science ®Google Scholar
• Besl P, McKay N. A method for registration of 3-D shapes. IEEE Trans Pattern Anal Machine Intell 1992; 14(2)239–256
   Web of Science ®Google Scholar
• Moreno A, Delso G, Camara O, Bloch I. Non-linear registration between 3D images including rigid objects: Application to CT and PET lung images with tumors. Proceedings of Workshop on Image Registration in Deformable Environments (DEFORM ’06), EdinburghUK, September, 2006, 31–40
   Google Scholar
• Bookstein F. Principal Warps: Thin-plate splines and the decomposition of deformations. IEEE Trans Pattern Anal Machine Intell 1989; 11(6)567–585
   Web of Science ®Google Scholar