3D ultrasound-CT registration of the liver using combined landmark-intensity information (original) (raw)

• Bakalakos E, Kim J, Young D et al (1998) Determinants of survival following hepatic resection for metastatic colorectal cancer. World J Surg 22: 399–404
  Article PubMed CAS Google Scholar
• Fong Y, Fortner J, Sun R et al (1999) Clinical score for predicting recurrence after hepatic resection for metastatic colorectal cancer: analysis of 1001 consecutive cases. Ann Surg 230: 309–318
  Article PubMed CAS Google Scholar
• Abdalla E, Barnett C, Doherty D et al (2002) Extended hepatectomy in patients with hepatobiliary malignancies with and without preoperative portal vein embolization. Arch Surg 137: 675–680
  Article PubMed Google Scholar
• Shirabe K, Shimada M, Gion T et al (1999) Postoperative liver failure after major hepatic resection for hepatocellular carcinoma in the modern era with special reference to remnant liver volume. J Am Coll Surg 188: 304–309
  Article PubMed CAS Google Scholar
• Shoup M, Gonen M, D’Angelica M et al (2003) Volumetric analysis predicts hepatic dysfunction in patients undergoing major liver resection. J Gastrointest Surg 7: 325–330
  Article PubMed Google Scholar
• Vauthey J, Chaoui A, Do K et al (2000) Standardized measurement of the future liver remnant prior to extended liver resection: methodology and clinical associations. Surgery 127: 512–519
  Article PubMed CAS Google Scholar
• Redaelli C, Wagner M, Krahenbuhl L et al (2002) Liver surgery in the era of tissue-preserving resections: early and late outcome in patients with primary and secondary hepatic tumors. World J Surg 26: 1126–1132
  Article PubMed Google Scholar
• Selle D, Preim B, Schenk A, Peitgen HO (2002) Analysis of vasculature for liver surgical planning. IEEE Trans Med Imaging 21(11): 1344–1357
  Article PubMed Google Scholar
• Lang H, Radtke A, Hindennach M, Schroeder T, Fruhauf NR, Malago M et al (2005) Impact of virtual tumor resection and computer-assisted risk analysis on operation planning and intraoperative strategy in major hepatic resection. Arch Surg 140(7): 629–638
  Article PubMed Google Scholar
• Cash DM, Miga MI, Glasgow SC, Dawant BM, Clements LW, Cao Z et al (2007) Concepts and Preliminary Data Toward the Realization of Image-guided Liver Surgery. J Gastrointest Surg 11(7): 844–859
  Article PubMed Google Scholar
• Birth M, Kleemann M, Hildebrand P, Bruch HP (2004) Intraoperative online navigation of dissection of the hepatical tissue—a new dimension in liver surgery. In: CARS, pp 770–774
• Beller S, Hünerbein M, Eulenstein S, Lange T, Schlag P (2007) Feasibility of navigated resection of liver tumors using multiplanar visualization of intraoperative 3D ultrasound data. Ann Surg 246(2): 288–294
  Article PubMed Google Scholar
• Beller S, Hünerbein M, Lange T, Eulenstein S, Gebauer B, Schlag PM (2007) Image-guided surgery of liver metastases by 3D ultrasound-based optoelectronic navigation. Brit J Surg 94(7): 866–875
  Article PubMed CAS Google Scholar
• Roche A, Pennec X, Malandain G, Ayache N (2001) Rigid registration of 3-D ultrasound with MR images: a new approach combining intensity and gradient information. IEEE Trans Med Imaging 20(10): 1038–1049
  Article PubMed CAS Google Scholar
• Slomka PJ, Mandel J, Downey D, Fenster A (2001) Evaluation of voxel-based registration of 3-D power Doppler ultrasound and 3-D magnetic resonance angiographic images of carotid arteries. Ultrasound Med Biol 27(7): 945–955
  Article PubMed CAS Google Scholar
• Porter BC, Rubens DJ, Strang JG, Smith J, Totterman S, Parker KJ (2001) Three-dimensional registration and fusion of ultrasound and MRI using major vessels as fiducial markers. IEEE Trans Med Imaging 20(4): 354–359
  Article PubMed CAS Google Scholar
• Penney GP, Blackall JM, Hamady MS, Sabharwal T, Adam A, Hawkes DJ (2004) Registration of freehand 3D ultrasound and magnetic resonance liver images. Med Image Anal 8(1): 81–91
  Article PubMed CAS Google Scholar
• Lange T, Eulenstein S, Hünerbein M, Schlag PM (2003) Vessel-based non-rigid registration of MR/CT and 3D ultrasound for navigation in liver surgery. Comput Aided Surg 8(5): 228–240
  Article PubMed Google Scholar
• Lange T, Eulenstein S, Hünerbein M, Lamecker H, Schlag P (2004) Augmenting intraoperative 3D ultrasound with preoperative models for navigation in liver surgery. In: Barillot C, Haynor D, Hellier P (eds) Medical image computing and computer-assisted intervention. Lecture notes in computer science, vol 3217. Springer, Berlin, pp 534–541
  Google Scholar
• Reinertsen I, Lindseth F, Unsgaard G, Collins D (2007) Clinical validation of vessel-based registration for correction of brain-shift. Med Image Anal (in press)
• Reinertsen I, Descoteaux M, Siddiqi K, Collins D (2007) Validation of vessel-based registration for correction of brain shift. Med Image Anal 11(4): 374–388
  Article PubMed CAS Google Scholar
• Aylward SR, Jomier J, Weeks S, Bullitt E (2003) Registration and analysis of vascular images. Int J Comput Vision 55(2–3): 123–138
  Article Google Scholar
• Lange T, Lamecker H, Hünerbein M, Eulenstein S, Beller S, Schlag P et al (2007) A distance measure for non-rigid registration of geometrical models to intensity data. In: Lemke H et al (eds) CARS, vol 2 (Supp 1) of International Journal of Computer Assisted Radiology and Surgery. Springer, Berlin, pp 204–206
  Google Scholar
• Haber E, Modersitzki J (2004) Numerical methods for volume preserving image registration. Inverse Probl 20: 1621–1638
  Article Google Scholar
• Modersitzki J (2007) Image registration with local rigidity constraints. In: Bildverarbeitung für die Medizin, pp 444–448
• Gobbi D, Comeau R, Peters T (2000) Ultrasound/mri overlay with image warping for neurosurgery. In: Medical Image Computing and Computer-Assisted Intervention (MICCAI). Springer, Berlin, pp 106–114
• Bookstein FL (1989) Principal warps: thin-plate splines and the decomposition of deformations. IEEE Trans Pattern Anal Mach Intell 11(6): 567–585
  Article Google Scholar
• Rohr K (2001) Landmark-based image analysis. Springer, Berlin
  Google Scholar
• Modersitzki J (2004) Numerical methods for image registration. Oxford University Press, Oxford
  Google Scholar
• Davis MH, Khotanzad A, Flaming DP, Harms SE (1997) A physics-based coordinate transformation for 3-D image matching. IEEE Trans Med Imaging 16(3): 317–328
  Article PubMed CAS Google Scholar
• Kohlrausch J, Rohr K, Stiehl HS (2005) A new class of elastic body splines for nonrigid registration of medical images. J Math Imaging Vis 23: 253–280
  Article Google Scholar
• Rohr K, Stiehl H, Sprengel R, Buzug T, Weese J, Kuhn M (2001) Landmark-based elastic registration using approximating thin-plate splines. IEEE Trans Med Imag 20(6): 526–534
  Article CAS Google Scholar
• Wörz S, Rohr K (2006) Physics-based elastic image registration using splines and including landmark localization uncertainties. In: MICCAI (2), pp 678–685
• Papenberg N, Lange T, Modersitzki J, Schlag PM, Fischer B (2008) Image registration for CT and intra-operative ultrasound data of the liver. In: SPIE Medical imaging: visualization, image-guided procedures, and modeling, vol 6918 (accepted)
• Fischer B, Modersitzki J (2003) Combining landmarks and intensity driven registrations. In: PAMM Proceedings in Applied Mathematics and Mechanics. vol 3, pp 32–35
• Fischer B, Modersitzki J (2003) Combination of automatic non-rigid and landmark based registration: the best of both worlds. In: Sonka M, Fitzpatrick J (eds) Medical imaging 2003: image processing. Proceedings of the SPIE 5032, vol 5032, pp 1037–1048
• Haber E, Modersitzki J (2007) Intensity gradient based registration and fusion of multi-modal images. Methods Inf Med 46(3): 292–299
  PubMed Google Scholar
• Fischer B, Modersitzki J (2003) FLIRT: a flexible image registration toolbox. In: Gee J, Maintz J, Vannier M (eds) 2nd International Workshop on Biomedical Image Registration 2003, vol 2717. Springer, Berlin, pp 261–270
  Google Scholar
• Papenberg N, Schumacher H, Heldmann S, Wirtz S, Bommersheim S, Ens K et al (2007) A fast and flexible image registration toolbox—design and implementation of the general approach. Bildverarbeitung für die Medizin 2007. Informatik Aktuell, pp 106–110
• Broit C (1981) Optimal registration of deformed images. Department of Computer and Information Science, University of Pennsylvania
• Haber E, Modersitzki J (2006) A multilevel method for image registration. SIAM J Sci Comput 27(5): 1594–1607
  Article Google Scholar
• Modersitzki J (2008) FLIRT with rigidity—image registration with a local non-rigidity penalty. Int J Comput Vis 76(2): 153–163
  Article Google Scholar
• Wahba G (1990) Spline models for observational data. SIAM, Philadelphia
• Nocedal J, Wright SJ (1999) Numerical optimization. Springer, Berlin
  Google Scholar
• Lange T, Wenckebach T, Lamecker H, Seebass M, Hünerbein M, Eulenstein S et al (2005) Registration of different phases of constrast-enhanced CT/MRI data for computer-assisted liver surgery planning: Evaluation of state-of-the-art methods. Int J Med Robot Comput Assist Surg 1(3): 6–20
  Article CAS Google Scholar
• Christensen G, Geng X, Kuhl J, Bruss J, Grabowski T, Pirwani I et al (2006) Introduction to the non-rigid image registration evaluation project (NIREP). In: WBIR. Lecture notes in computer science, vol 4057. Springer, Berlin, pp 128–135
• Lange T, Lamecker H, Hünerbein M, Eulenstein S, Beller S, Schlag PM (2008) Validation metrics for non-rigid registration of medical images containing vessel trees. In: Bildverarbeitung für die Medizin (BVM), pp 82–86