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Proceedings Paper

Breast deformation modelling: comparison of methods to obtain a patient specific unloaded configuration
Author(s): Björn Eiben; Vasileios Vavourakis; John H. Hipwell; Sven Kabus; Cristian Lorenz; Thomas Buelow; David J. Hawkes
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Paper Abstract

In biomechanical simulations of the human breast, the analysed geometry is often reconstructed from in vivo medical imaging procedures. For example in dynamic contrast enhanced magnetic resonance imaging, the acquired geometry of the patient's breast when lying in the prone position represents a deformed configuration that is pre-stressed by typical in vivo conditions and gravity. Thus, physically realistic simulations require consideration of this loading and, hence, establishing the undeformed configuration is an important task for accurate and reliable biomechanical modelling of the breast. We compare three different numerical approaches to recover the unloaded configuration from the loaded geometry given patient-specific biomechanical models built from prone and supine MR images. The algorithms compared are:(i) the simple inversion of gravity without the consideration of pre-stresses, (ii) an inversefinite deformation approach and (iii) afixed point type iterative approach which uses only forward simulations. It is shown that the iterative and the inverse approach produce similar zero-gravity estimates, where as the simple inversion of gravity is only appropriate for small or highly constrained deformations.

Paper Details

Date Published: 12 March 2014
PDF: 8 pages
Proc. SPIE 9036, Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling, 903615 (12 March 2014); doi: 10.1117/12.2043607
Show Author Affiliations
Björn Eiben, Univ. College London (United Kingdom)
Vasileios Vavourakis, Univ. College London (United Kingdom)
John H. Hipwell, Univ. College London (United Kingdom)
Sven Kabus, Philips Research (Germany)
Cristian Lorenz, Philips Research (Germany)
Thomas Buelow, Philips Research (Germany)
David J. Hawkes, Univ. College London (United Kingdom)


Published in SPIE Proceedings Vol. 9036:
Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling
Ziv R. Yaniv; David R. Holmes, Editor(s)

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