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. 2012 Jul;16(5):966-75.
doi: 10.1016/j.media.2012.03.001. Epub 2012 Mar 28.

MRI to X-ray mammography registration using a volume-preserving affine transformation

Thomy Mertzanidou  1 , John Hipwell, M Jorge Cardoso, Xiying Zhang, Christine Tanner, Sebastien Ourselin, Ulrich Bick, Henkjan Huisman, Nico Karssemeijer, David Hawkes
Affiliations

MRI to X-ray mammography registration using a volume-preserving affine transformation

Thomy Mertzanidou et al. Med Image Anal. 2012 Jul.

Abstract

X-ray mammography is routinely used in national screening programmes and as a clinical diagnostic tool. Magnetic Resonance Imaging (MRI) is commonly used as a complementary modality, providing functional information about the breast and a 3D image that can overcome ambiguities caused by the superimposition of fibro-glandular structures associated with X-ray imaging. Relating findings between these modalities is a challenging task however, due to the different imaging processes involved and the large deformation that the breast undergoes. In this work we present a registration method to determine spatial correspondence between pairs of MR and X-ray images of the breast, that is targeted for clinical use. We propose a generic registration framework which incorporates a volume-preserving affine transformation model and validate its performance using routinely acquired clinical data. Experiments on simulated mammograms from 8 volunteers produced a mean registration error of 3.8±1.6mm for a mean of 12 manually identified landmarks per volume. When validated using 57 lesions identified on routine clinical CC and MLO mammograms (n=113 registration tasks) from 49 subjects the median registration error was 13.1mm. When applied to the registration of an MR image to CC and MLO mammograms of a patient with a localisation clip, the mean error was 8.9mm. The results indicate that an intensity based registration algorithm, using a relatively simple transformation model, can provide radiologists with a clinically useful tool for breast cancer diagnosis.

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