Predicting tumour location by simulating large deformations of the breast using a 3D finite element model and nonlinear elasticity

Two of the major imaging modalities used to detect and monitor breast cancer are (contrast enhanced) magnetic resonance (MR) imaging and mammography. Image fusion, including accurate registration between MR images and mammograms, or between CC and MLO mammograms, is increasingly key to patient manag...

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Main Authors: Pathmanathan, P, Gavaghan, D, Whiteley, J, Brady, M, Nash, M, Nielsen, P, Rajagopal, V
Format: Conference item
Published: 2004
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author Pathmanathan, P
Gavaghan, D
Whiteley, J
Brady, M
Nash, M
Nielsen, P
Rajagopal, V
author_facet Pathmanathan, P
Gavaghan, D
Whiteley, J
Brady, M
Nash, M
Nielsen, P
Rajagopal, V
author_sort Pathmanathan, P
collection OXFORD
description Two of the major imaging modalities used to detect and monitor breast cancer are (contrast enhanced) magnetic resonance (MR) imaging and mammography. Image fusion, including accurate registration between MR images and mammograms, or between CC and MLO mammograms, is increasingly key to patient management (for example in the multidisciplinary meeting), but registration is extremely difficult because the breast shape varies massively between the modalities, due both to the different postures of the patient for the two modalities and to the fact that the breast is forcibly compressed during mammography. In this paper, we develop a 3D, patient-specific, anatomically accurate, finite element model of the breast using MR images, which can be deformed in a physically realistic manner using nonlinear elasticity theory to simulate the breast during mammography. © Springer-Verlag Berlin Heidelberg 2004.
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spelling oxford-uuid:121acb4e-5d40-485d-b937-0c42df10bf542022-03-26T10:05:59ZPredicting tumour location by simulating large deformations of the breast using a 3D finite element model and nonlinear elasticityConference itemhttp://purl.org/coar/resource_type/c_5794uuid:121acb4e-5d40-485d-b937-0c42df10bf54Symplectic Elements at Oxford2004Pathmanathan, PGavaghan, DWhiteley, JBrady, MNash, MNielsen, PRajagopal, VTwo of the major imaging modalities used to detect and monitor breast cancer are (contrast enhanced) magnetic resonance (MR) imaging and mammography. Image fusion, including accurate registration between MR images and mammograms, or between CC and MLO mammograms, is increasingly key to patient management (for example in the multidisciplinary meeting), but registration is extremely difficult because the breast shape varies massively between the modalities, due both to the different postures of the patient for the two modalities and to the fact that the breast is forcibly compressed during mammography. In this paper, we develop a 3D, patient-specific, anatomically accurate, finite element model of the breast using MR images, which can be deformed in a physically realistic manner using nonlinear elasticity theory to simulate the breast during mammography. © Springer-Verlag Berlin Heidelberg 2004.
spellingShingle Pathmanathan, P
Gavaghan, D
Whiteley, J
Brady, M
Nash, M
Nielsen, P
Rajagopal, V
Predicting tumour location by simulating large deformations of the breast using a 3D finite element model and nonlinear elasticity
title Predicting tumour location by simulating large deformations of the breast using a 3D finite element model and nonlinear elasticity
title_full Predicting tumour location by simulating large deformations of the breast using a 3D finite element model and nonlinear elasticity
title_fullStr Predicting tumour location by simulating large deformations of the breast using a 3D finite element model and nonlinear elasticity
title_full_unstemmed Predicting tumour location by simulating large deformations of the breast using a 3D finite element model and nonlinear elasticity
title_short Predicting tumour location by simulating large deformations of the breast using a 3D finite element model and nonlinear elasticity
title_sort predicting tumour location by simulating large deformations of the breast using a 3d finite element model and nonlinear elasticity
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