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Publication Detail
Anisotropic multi-scale fluid registration: evaluation in magnetic resonance breast imaging
  • Publication Type:
    Journal article
  • Publication Sub Type:
  • Authors:
    Crum WR, Tanner C, Hawkes DJ
  • Publisher:
    Institute of Physics Publishing
  • Publication date:
  • Pagination:
    5153, 5174
  • Journal:
    Physics in Medicine and Biology
  • Volume:
  • Issue:
  • Print ISSN:
  • Keywords:
    Algorithms, Anisotropy, Breast, Female, Humans, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, London, Magnetic Resonance Spectroscopy, methods, Models, Statistical, pathology, Phantoms, Imaging, Radiographic Image Enhancement, Reproducibility of Results, Research Support, Non-U.S.Gov't, Time Factors
  • Addresses:
    Centre for Medical Image Computing (CMIC), University College London, London, WC1E 6BT, UK. b.crum@ucl.ac.uk
  • Notes:
    DA - 20051020
Registration using models of compressible viscous fluids has not found the general application of some other techniques (e.g. free-form-deformation (FFD)) despite its ability to model large diffeomorphic deformations. We report on a multi-resolution fluid registration algorithm which improves on previous work by (a) directly solving the Navier-Stokes equation at the resolution of the images, (b) accommodating image sampling anisotropy using semicoarsening and implicit smoothing in a full multi-grid (FMG) solver and (c) exploiting the inherent multi-resolution nature of FMG to implement a multi-scale approach. Evaluation is on five magnetic resonance (MR) breast images subject to six biomechanical deformation fields over 11 multi-resolution schemes. Quantitative assessment is by tissue overlaps and target registration errors and by registering using the known correspondences rather than image features to validate the fluid model. Context is given by comparison with a validated FFD algorithm and by application to images of volunteers subjected to large applied deformation. The results show that fluid registration of 3D breast MR images to sub-voxel accuracy is possible in minutes on a 1.6 GHz Linux-based Athlon processor with coarse solutions obtainable in a few tens of seconds. Accuracy and computation time are comparable to FFD techniques validated for this application.
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