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Abstract #3310

Joint Elasticity Reconstruction and Displacement Filtering for 3D Magnetic Resonance Elastography

Shahed Khan Mohammed1, Mohammad Honarvar1, Davood Karimi1, Piotr Kozlowski2,3, and Septimiu Salcudean1
1Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada, 2UBC MRI Research Center, Vancouver, BC, Canada, 3Department of Radiology, University of British Columbia, Vancouver, BC, Canada

Iterative reconstruction methods in magnetic resonance elastography (MRE) inversion can allow incorporating sparsity prior and can provide displacement filtering. However the problem is difficult to converge as MRE inversion is a non-convex and ill-conditioned problem. Here, we presented 3D ERBA with total variation prior on the elasticity, which showed good convergence by utilizing a bi-convex optimization of 3D finite element modeling of elastic wave. Extensive experiments on numerical phantom, agar phantom, and in-vivo liver study showed promising indications in detecting inclusion and abnormality, and improving the diagnostic efficacy of MRE.

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