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Tanner, C.* ; Degenhard, A.* ; Schnabel, J.A.* ; Castellano-Smith, A.D.* ; Hayes, C.* ; Sonoda, L.I.* ; Leach, M.O.* ; Hose, D.R.* ; Hill, D.L.G.* ; Hawkes, D.J.*

Comparison of biomechanical breast models: A case study.

Proc. SPIE 4684 III, 1807-1818 (2002)
DOI
Open Access Green as soon as Postprint is submitted to ZB.
We present initial results from evaluating the accuracy with which biomechanical breast models based on finite element methods can predict the displacements of tissue within the breast. We investigate the influence of different tissue elasticity values, Poisson's ratios, boundary conditions, finite element solvers and mesh resolutions on one data set. MR images were acquired before and after compressing a volunteer's breast gently. These images were aligned using a 3D non-rigid registration algorithm. The boundary conditions were derived from the result of the non-rigid registration or by assuming no patient motion at the deep or medial side. Three linear and two non-linear elastic material models were tested. The accuracy of the BBMs was assessed by the Euclidean distance of twelve corresponding anatomical landmarks. Overall, none of the tested material models was obviously superior to another regarding the set of investigated values. A major average error increase was noted for partially inaccurate boundary conditions at high Poisson's ratios due to introduced volume change. Maximal errors remained, however, high for low Poisson's ratio due to the landmarks closeness to the inaccurate boundary conditions. The choice of finite element solver or mesh resolution had almost no effect on the performance outcome. © 2002 SPIE · 1605-7422/02/$15.00.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Biomechanical Models ; Breast Deformation ; Finite Element Methods ; Non-rigid Registration
ISSN (print) / ISBN 0277-786X
e-ISSN 1996-756X
Journal Proceedings of SPIE
Quellenangaben Volume: 4684 III, Issue: , Pages: 1807-1818 Article Number: , Supplement: ,
Publisher SPIE
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute for Machine Learning in Biomed Imaging (IML)