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
Consistency of parametric registration in serial MRI studies of brain tumor progression
  • Publication Type:
    Journal article
  • Publication Sub Type:
  • Authors:
    Mang A, Schnabel JA, Crum WR, Modat M, Camara-Rey O, Palm C, Caseira GB, Jager HR, Ourselin S, Buzug TM, Hawkes DJ
  • Publication date:
  • Pagination:
  • Journal:
    International Journal of Computer Assisted Radiology and Surgery
  • Volume:
  • Notes:
    date-added: 2009-04-15 13:51:47 +0100 date-modified: 2009-11-04 17:51:55 +0000 local-url: file://localhost/Users/mmodat/Documents/Papers/2008Mang-1.pdf uri: papers://0E4B006B-D044-4501-93CA-AAE1F0F87354/Paper/p1144 rating: 0
Object The consistency of parametric registration in multitemporal magnetic resonance (MR) imaging studies was evaluated. Materials and methods Serial MRI scans of adult patients with a brain tumor (glioma) were aligned by parametric registration. The performance of low-order spatial alignment (6/9/12 degrees of freedom) of different 3D serial MR-weighted images is evaluated. A registration protocol for the alignment of all images to one reference coordinate system at baseline is presented. Registration results were evaluated for both, multimodal intra-timepoint and mono-modal multi-temporal registration. The latter case might present a challenge to automatic intensity-based registration algorithms due to ill-defined correspondences. The performance of our algorithm was assessed by testing the inverse registration consistency. Four different similarity measures were evaluated to assess consistency. Results Careful visual inspection suggests that images are well aligned, but their consistency may be imperfect. Subvoxel inconsistency within the brain was found for all similarity measures used for parametric multi-temporal registration. T1-weighted images were most reliable for establishing spatial correspondence between different timepoints. Conclusions The parametric registration algorithm is feasible for use in this application. The sub-voxel resolution mean displacement error of registration transformations demonstrates that the algorithm converges to an almost identical solution for forward and reverse registration.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Dept of Med Phys & Biomedical Eng
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