Document Detail


MRI to X-ray mammography registration using a volume-preserving affine transformation.
MedLine Citation:
PMID:  22513136     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
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.
Authors:
Thomy Mertzanidou; John Hipwell; M Jorge Cardoso; Xiying Zhang; Christine Tanner; Sebastien Ourselin; Ulrich Bick; Henkjan Huisman; Nico Karssemeijer; David Hawkes
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-3-28
Journal Detail:
Title:  Medical image analysis     Volume:  -     ISSN:  1361-8423     ISO Abbreviation:  -     Publication Date:  2012 Mar 
Date Detail:
Created Date:  2012-4-19     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9713490     Medline TA:  Med Image Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012 Elsevier B.V. All rights reserved.
Affiliation:
Centre for Medical Image Computing, University College London, Gower Street, London WC1E 6BT, UK.
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