Abstract
We present a novel validation method for non-rigid registration using a simulation of deformations based on biomechanical modelling of tissue properties. This method is tested on a previously developed non-rigid registration method for dynamic contrast enhanced Magnetic Resonance (MR) mammography image pairs [1]. We have constructed finite element breast models and applied a range of displacements to them, with an emphasis on generating physically plausible deformations which may occur during normal patient scanning procedures. From the finite element method (FEM) solutions, we have generated a set of deformed contrast enhanced images against which we have registered the original dynamic image pairs. The registration results have been successfully validated at all breast tissue locations by comparing the recovered displacements with the biomechanical displacements. The validation method presented in this paper is an important tool to provide biomechanical gold standard deformations for registration error quantification, which may also form the basis to improve and compare different non-rigid registration techniques for a diversity of medical applications.
Acknowledgements
The authors would like to thank Dr. Luke Sonoda from CISG, and Dr. Erica Denton and Dr. Sheila Rankin from Guy’s Hospital for access to the image database, Dr. Frans Gerritsen and Marcel Quist from Philips Medical Systems, Dr. Daniel Rueckert from Imperial College London for useful discussions, and Dr. Philippe Batchelor from CISG and Justin Penrose from the University of Sheffield for their help in the model construction. The work on biomechanical tissue modelling using ANSYS was funded by EPSRC, and segmentations were carried out using ANALYZE. JAS has received funding from Philips Medical Systems, EasyVision Advanced Development. CT and ADCS have received funding from EPSRC grants GR/M52779 and GR/M47294, respectively.
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Schnabel, J.A. et al. (2001). Validation of Non-rigid Registration Using Finite Element Methods. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_34
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DOI: https://doi.org/10.1007/3-540-45729-1_34
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