Using statistical deformation models for the registration of multimodal breast images

Christine Tanner; John H. Hipwell; David J. Hawkes

doi:10.1117/12.811631

27 March 2009 Using statistical deformation models for the registration of multimodal breast images

Christine Tanner, John H. Hipwell, David J. Hawkes

Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 72590P (2009) https://doi.org/10.1117/12.811631
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

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).

Citation Download Citation

Christine Tanner, John H. Hipwell, and David J. Hawkes "Using statistical deformation models for the registration of multimodal breast images", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72590P (27 March 2009); https://doi.org/10.1117/12.811631

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