title: MRI to X-ray mammography intensity-based registration with simultaneous optimisation of pose and biomechanical transformation parameters.
abstract: Determining corresponding regions between an MRI and an X-ray mammogram is a clinically useful task that is challenging for radiologists due to the large deformation that the breast undergoes between the two image acquisitions. In this work we propose an intensity-based image registration framework, where the biomechanical transformation model parameters and the rigid-body transformation parameters are optimised simultaneously. Patient-specific biomechanical modelling of the breast derived from diagnostic, prone MRI has been previously used for this task. However, the high computational time associated with breast compression simulation using commercial packages, did not allow the optimisation of both pose and FEM parameters in the same framework. We use a fast explicit Finite Element (FE) solver that runs on a graphics card, enabling the FEM-based transformation model to be fully integrated into the optimisation scheme. The transformation model has seven degrees of freedom, which include parameters for both the initial rigid-body pose of the breast prior to mammographic compression, and those of the biomechanical model. The framework was tested on ten clinical cases and the results were compared against an affine transformation model, previously proposed for the same task. The mean registration error was 11.6±3.8mm for the CC and 11±5.4mm for the MLO view registrations, indicating that this could be a useful clinical tool.
authors.affiliation: Centre for Medical Image Computing, University College London, Gower Street, WC1E 6BT London, UK. Electronic address: t.mertzanidou@cs.ucl.ac.uk.
authors.forename: Thomy
authors.initials: T
authors.lastname: Mertzanidou
authors.affiliation: Centre for Medical Image Computing, University College London, Gower Street, WC1E 6BT London, UK.
authors.forename: John
authors.initials: J
authors.lastname: Hipwell
authors.affiliation: Centre for Medical Image Computing, University College London, Gower Street, WC1E 6BT London, UK.
authors.forename: Stian
authors.initials: S
authors.lastname: Johnsen
authors.affiliation: Centre for Medical Image Computing, University College London, Gower Street, WC1E 6BT London, UK.
authors.forename: Lianghao
authors.initials: L
authors.lastname: Han
authors.affiliation: Centre for Medical Image Computing, University College London, Gower Street, WC1E 6BT London, UK.
authors.forename: Bjoern
authors.initials: B
authors.lastname: Eiben
authors.affiliation: Department of Mechanical Engineering, The University of Sheffield, Mappin Street, S1 3JD Sheffield, UK.
authors.forename: Zeike
authors.initials: Z
authors.lastname: Taylor
authors.affiliation: Centre for Medical Image Computing, University College London, Gower Street, WC1E 6BT London, UK.
authors.forename: Sebastien
authors.initials: S
authors.lastname: Ourselin
authors.affiliation: Diagnostic Image Analysis Group, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
authors.forename: Henkjan
authors.initials: H
authors.lastname: Huisman
authors.affiliation: Department of Radiology, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
authors.forename: Ritse
authors.initials: R
authors.lastname: Mann
authors.affiliation: Department of Radiology, Charite Universitätsmedizin Berlin, 10117 Berlin, Germany.
authors.forename: Ulrich
authors.initials: U
authors.lastname: Bick
authors.affiliation: Diagnostic Image Analysis Group, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
authors.forename: Nico
authors.initials: N
authors.lastname: Karssemeijer
authors.affiliation: Centre for Medical Image Computing, University College London, Gower Street, WC1E 6BT London, UK.
authors.forename: David
authors.initials: D
authors.lastname: Hawkes
mesh_terms: D001696:Biomechanical Phenomena; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008327:Mammography / Q000379:methods*; D008962:Models, Theoretical
keywords: Breast imaging; FEM-based transformation model; Mammography; Multimodal registration