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Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography

Sangtae Ahn1, Abhijit J Chaudhari1,3, Felix Darvas1,4, Charles A Bouman2 and Richard M Leahy1

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We investigate fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography for applications in small animal imaging. Our forward model uses a diffusion approximation for optically inhomogeneous tissue, which we solve using a finite element method (FEM). We examine two approaches to incorporating the forward model into the solution of the inverse problem. In a conventional direct calculation approach one computes the full forward model by repeated solution of the FEM problem, once for each potential source location. We describe an alternative on-the-fly approach where one does not explicitly solve for the full forward model. Instead, the solution to the forward problem is included implicitly in the formulation of the inverse problem, and the FEM problem is solved at each iteration for the current image estimate. We evaluate the convergence speeds of several representative iterative algorithms. We compare the computation cost of those two approaches, concluding that the on-the-fly approach can lead to substantial reductions in total cost when combined with a rapidly converging iterative algorithm.


PACS

87.63.L- Visual imaging

02.60.Ed Interpolation; curve fitting

07.05.Pj Image processing

02.70.Dh Finite-element and Galerkin methods

87.57.N- Image analysis

02.30.Zz Inverse problems

Subjects

Mathematical physics

Computational physics

Instrumentation and measurement

Medical physics

Dates

Issue 14 (21 July 2008)

Received 11 August 2007, in final form 3 June 2008

Published 1 July 2008



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