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Proceedings Paper

Using statistical deformation models for the registration of multimodal breast images
Author(s): Christine Tanner; John H. Hipwell; David J. Hawkes
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Paper Abstract

This paper describes a novel method for registering multimodal breast images. The method is based on guiding initial alignment by a 3D statistical deformation model (SDM) followed by a standard non-rigid registration method for fine alignment. The method was applied to the problem of compensating for large breast compressions, namely registering magnetic resonance (MR) images to tomosynthesis images and X-ray mammograms. The SDM was based on simulating plausible breast compressions for a population of 20 subjects via finite element models created from segmented 3D MR breast images. Leave-one-out tests on simulated data showed that using SDM guided registration rather than affine registration for the initial alignment led on average to lower mean registration errors, namely 3.2 mm versus 4.2 mm for MR to tomosynthesis images (17.1 mm initially) and 5.0 mm versus 6.2 mm for MR to X-ray mammograms (15.0 mm initially).

Paper Details

Date Published: 27 March 2009
PDF: 9 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72590P (27 March 2009); doi: 10.1117/12.811631
Show Author Affiliations
Christine Tanner, Ctr. for Medical Image Computing, Univ. College London (United Kingdom)
John H. Hipwell, Ctr. for Medical Image Computing, Univ. College London (United Kingdom)
David J. Hawkes, Ctr. for Medical Image Computing, Univ. College London (United Kingdom)


Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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