NAMay 21, 2017
Accelerating optimization-based computed tomography via sparse matrix approximationsRichard C. Barnard, Rick Archibald
Variational formulations of reconstruction in computed tomography have the notable drawback of requiring repeated evaluations of both the forward Radon transform and either its adjoint or an approximate inverse transform which are relatively expensive. We look at two methods for reducing the effect of this resulting computational bottleneck via approximating the transform evaluation with sparse matrix multiplications. The first method is applicable for general iterative optimization algorithms. The second is applicable in error-forgetting algorithms such as split Bregman. We demonstrate these approximations significantly reduce the needed computational time needed for the iterative algorithms needed to solve the reconstruction problem while still providing good reconstructions.
NAOct 21, 2014
Sensitivity analysis for dose deposition in radiotherapy via a Fokker-Planck modelRichard C. Barnard, Martin Frank, Kai Krycki
In this paper we study the sensitivities of electron dose calculations with respect to the stopping power and the transport coefficients. We focus on the application to radiotherapy simulations. We use a Fokker-Planck approximation to the Boltzmann transport equation. Equations for the sensitivities are derived by the adjoint method. The Fokker-Planck equation and its adjoint are solved numerically in slab geometry using the spherical harmonics expansion ($P_N$) and an HLL finite volume method. Our method is verified by comparison to finite difference approximations of the sensitivities. Finally, we present numerical results of the sensitivities for the normalized average dose deposition depth with respect to the stopping power and transport coefficients, demonstrating the increasing relative sensitivities as beam energy decreases.