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 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
Respiratory motion correction in dynamic MRI using Robust Data Decomposition Registration – Application to DCE-MRI
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Hamy V, Dikaios N, Punwani S, Melbourne A, Latifoltojar A, Makanyanga J, Chouhan M, Helbren E, Menys A, Taylor S, Atkinson D
  • Publication date:
    02/2014
  • Pagination:
    301, 313
  • Journal:
    Medical Image Analysis
  • Volume:
    18
  • Issue:
    2
  • Status:
    Published
  • Keywords:
    Registration, respiratory motion correction, robust principal component analysis, dynamic contrast-enhanced MRI
Abstract
Motion correction in Dynamic Contrast Enhanced (DCE-) MRI is challenging because rapid intensity changes can compromise common (intensity based) registration algorithms. In this study we introduce a novel registration technique based on robust principal component analysis (RPCA) to decompose a given time-series into a low rank and a sparse component. This allows robust separation of motion components that can be registered, from intensity variations that are left unchanged. This Robust Data Decomposition Registration (RDDR) is demonstrated on both simulated and a wide range of clinical data. Robustness to different types of motion and breathing choices during acquisition is demonstrated for a variety of imaged organs including liver, small bowel and prostate. The analysis of clinically relevant regions of interest showed both a decrease of error (15-62% reduction following registration) in tissue time-intensity curves and improved areas under the curve (AUC60) at early enhancement.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Author
Experimental & Translational Medicine
Author
Experimental & Translational Medicine
Author
Experimental & Translational Medicine
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by