Medical Dosimetry
Volume 34, Issue 4 , Pages 317-322 , Winter 2009

Evaluation of Four Volume-Based Image Registration Algorithms

Received 12 May 2008 ,Accepted 11 December 2008.

References 

  1. Hallpike L, Hawkes DJ. Medical image registration: An overview. Imaging. 2002;14:455–463
  2. Hill DLG, Batchelar PG, Holden M, et al. Medical image registration. Phys. Med. Biol. 2001;46:R1–R45
  3. Kagadis GC, Delibasis KK, Matsopoulos GK, et al. A comparative study of surface- and volume-based techniques for the automatic registration between CT and SPECT brain images. Med. Phys. 2002;29:201–213
  4. Maurer CR, Fitzpatrick JM, Wang MY, et al. Registration of head volume images using implantable fiducial markers. IEEE. Trans. Med. Imaging. 1997;16:447–462
  5. Besl PJ, McKay ND. A method for registration of 3-D shapes. IEEE. Trans. Pattern. Anal. Mach. Intell. 1992;14:239–256
  6. Borgefors G. Hierarchical chamfer matching: A parametric edge matching algorithm. IEEE. Trans. Pattern. Ana. Mach. Intell. 1988;10:849–865
  7. Cai J, Chu JCH, Recine D, et al. CT and PET lung image registration and fusion in radiotherapy treatment planning using the chamfer-matching method. Int. J. Radiat. Oncol. Biol. Phys. 1999;43:883–891
  8. Maes F, Collingnon A, Vandermeulen D, et al. Multimodality image registration by maximization of mutual information. IEEE. Trans. Med. Imaging. 1997;16:187–198
  9. Studholme C, Hill DLG, Hawkes DJ. An overlap invariant entropy measure of 3D medical image alignment. Pattern. Recogn. 1999;32:71–86
  10. Wells WM, Voila P, Atsumi H, et al. Multi-modal volume registration by maximization of mutual information. Med. Image. Anal. 1996;1:35–51
  11. Rosch P, Netsch T, McNutt T, et al. Syntegra: Automatic image registration algorithms. Syntegra White Paper. Royal Philips Electronics; 2003;
  12. BrainScan Software Guide. 2001;BrainLab AG Germany
  13. West J, Fitzpatrick JM, Wang MY, et al. Comparison and evaluation of retrospective intermodality brain image registration techniques. J. Comput. Assist. Tomogr. 1997;21:554–566
  14. Crum WR, Camara O, Hill DLG. Generalized overlap measures for evaluation and validation in medical image analysis. IEEE. Trans. Med. Imag. 2006;25:1451–1461
  15. Leonid A, Teverovskiy OT, Carmichael HJ, et al. Feature-based vs. intensity-based brain image registration: Voxel level and structure level performance evaluation. Carnegie Mellon University, School of Computer Science, Technical Reports, CMU-ML-06-118. 2006;
  16. Van den Elsen PA, Pol EJD, Sumanaweera TS, et al. Grey value correlation techniques used for automatic matching of CT and MR brain and spine images. Proc. SPIE. 1994;2359:227–237
  17. Studholme C, Hill DLG, Hawkes DJ. Automatic 3D registration of MR and CT images of the head. Med. Image Anal. 1996;1:163–175
  18. Hill DLG, Hawkes DJ, Crossman J, et al. Registration of MR and CT images for skull base surgery using point-like anatomical features. Br. J. Radiol. 1991;64:1030–1035
  19. Lemieux L, Jagoe R. Effect of fiducial marker localization on stereotactic target coordinate calculation in CT slices and radiographs. Phys. Med. Biol. 1994;39:1915–1928
  20. Daisne J-F, Sibomana M, Bol A, et al. Evaluation of a multimodality image (CT, MRI and PET) coregistration procedure on phantom and head and neck cancer patients: Accuracy, reproducibility and consistency. Radiother. Oncol. 2003;69:237–245
  21. Murphy MJ. The importance of computed tomography slice thickness in radiographic patient positioning for radiosurgery. Med. Phys. 1999;26:171–175
  22. Muacevic A, Uhl E, Steiger HJ, et al. Accuracy and clinical applicability of a passive marker based frameless neuronavigation system. J. Clin. Neurosci. 2000;7:414–418
  23. Sugano N, Sasama T, Sato Y, et al. Accuracy evaluation of surface-based registration methods in a computer navigation system for hip surgery performed through a posterolateral approach. Comput. Aided. Surg. 2001;6:195–203

PII: S0958-3947(08)00201-X

doi: 10.1016/j.meddos.2008.12.004

Medical Dosimetry
Volume 34, Issue 4 , Pages 317-322 , Winter 2009