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 http://www.ucl.ac.uk/finance/research/post_award/post_award_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
Automatic correction of motion artifacts in magnetic resonance images using an entropy focus criterion
  • Publication Type:
    Journal article
  • Publication Sub Type:
  • Authors:
    Atkinson D, Hill DL, Stoyle PN, Summers PE, Keevil SF
  • Publisher:
    Institute of Electrical and Electronics Engineers
  • Publication date:
  • Pagination:
    903, 910
  • Journal:
    IEEE Transactions on Medical Imaging
  • Volume:
  • Issue:
  • Status:
  • Print ISSN:
  • Addresses:
    Image Processing Group, Radiological Sciences, UMDS, Guy's Hospital, London, UK
  • Notes:
    DA - 19980521
We present the use of an entropy focus criterion to enable automatic focusing of motion corrupted magnetic resonance images. We demonstrate the principle using illustrative examples from cooperative volunteers. Our technique can determine unknown patient motion or use knowledge of motion from other measures as a starting estimate. The motion estimate is used to compensate the acquired data and is iteratively refined using the image entropy. Entropy focuses the whole image principally by favoring the removal of motion induced ghosts and blurring from otherwise dark regions of the image. Using only the image data, and no special hardware or pulse sequences, we demonstrate correction for arbitrary rigid-body translational motion in the imaging plane and for a single rotation. Extension to three-dimensional (3-D) and more general motion should be possible. The algorithm is able to determine volunteer motion well. The mean absolute deviation between algorithm and navigator-echo-determined motion is comparable to the displacement step size used in the algorithm. Local deviations from the recorded motion or navigator-determined motion are explained and we indicate how enhanced focus criteria may be derived. In all cases we were able to compensate images for patient motion, reducing blurring and ghosting
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Experimental & Translational Medicine
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