UCL  IRIS
Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at https://www.ucl.ac.uk/finance/research/rs-contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Correcting scaling errors in tomographic images using a nine degree of freedom registration algorithm.
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Comparative Study
  • Authors:
    Hill DL, Maurer CR, Studholme C, Fitzpatrick JM, Hawkes DJ
  • Publication date:
    03/1998
  • Pagination:
    317, 323
  • Journal:
    J Comput Assist Tomogr
  • Volume:
    22
  • Issue:
    2
  • Status:
    Published
  • Country:
    United States
  • Print ISSN:
    0363-8715
  • Language:
    eng
  • Keywords:
    Algorithms, Brain, Calibration, Contrast Media, Diagnostic Errors, Gadolinium DTPA, Humans, Magnetic Resonance Imaging, Phantoms, Imaging, Tomography Scanners, X-Ray Computed, Tomography, X-Ray Computed
Abstract
PURPOSE: Clinical imaging systems, especially MR scanners, frequently have errors of a few percent in their voxel dimensions. We evaluate a nine degree of freedom registration algorithm that maximizes mutual information for determining scaling errors. We evaluate it by registering MR and CT images for each of five patients (patient scaling) and by registering MR images of a phantom to a computer model of the phantom (phantom scaling). METHOD: Each scaling method was validated using bone-implanted markers localized in the patient images and also intraoperatively. The root mean square residual in the alignment of the fiducial markers [fiducial registration error (FRE)] was determined without scale correction, with patient scaling, and with phantom scaling. RESULTS: Each scaling method significantly reduced the average FRE (p < 0.05) for MR to CT registration and for MR to physical space registration, indicating that voxel scaling errors were reduced. The greater reduction in scaling errors was achieved using the phantom scaling method. CONCLUSION: We have demonstrated that a nine degree of freedom registration algorithm that maximizes mutual information can significantly reduce scaling errors in MR.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Author
Dept of Med Phys & Biomedical Eng
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by