The possibility of application of the photon average trajectories (PAT) method to real-time reconstruction of tissue inhomogeneities in diffuse optical tomography of strongly scattering media has been substantiated. By this method, the inverse problem is reduced to solution of the integral equation with integration along a conditional PAT. Such an approach allows the standard fast algebraic algorithms commonly used in projection computed tomography to be applied to diffuse optical image reconstruction. To demonstrate the capabilities of the PAT method, a numerical experiment on cross-sectional reconstruction of cylindrical strongly scattering objects with absorbing inhomogeneities has been done. Relative shadows caused by inhomogeneities are simulated via numerical solution of the non-stationary diffusion equation. To solve the inverse problem, the QR-factorization least-squares algorithm and the multiplicative algebraic reconstruction technique are used. The results are compared with those obtained by a well-known software package for temporal optical absorption and scattering tomography based on multiple solution of the diffusion equation. It is shown that the PAT method allows reconstruction of the optical structure of objects with comparable accuracy while saving reconstruction time considerably.
We show that the scattering amplitude of four open string scalars or tachyons on the world-volume of a Dp-brane in the bosonic string theory can be written in a universal form. The difference between this amplitude and the corresponding amplitude in the superstring theory is in an extra tachyonic pole. We show that in an α expansion and for slowly varying fields, the amplitude is consistent with the tachyonic DBI action in which the even part of the tachyon potential is V (T ) = e −( √ πT /α) 2 with α = 1 for bosonic theory and α = √ 2 for superstring theory.
The possibility of improving the spatial resolution of diffuse optical tomograms reconstructed by the photon average trajectories (PAT) method is substantiated. The PAT method recently presented by us is based on a concept of an average statistical trajectory for transfer of light energy, the photon average trajectory (PAT). The inverse problem of diffuse optical tomography is reduced to a solution of an integral equation with integration along a conditional PAT. As a result, the conventional algorithms of projection computed tomography can be used for fast reconstruction of diffuse optical images. The shortcoming of the PAT method is that it reconstructs the images blurred due to averaging over spatial distributions of photons which form the signal measured by the receiver. To improve the resolution, we apply a spatially variant blur model based on an interpolation of the spatially invariant point spread functions simulated for the different small subregions of the image domain. Two iterative algorithms for solving a system of linear algebraic equations, the conjugate gradient algorithm for least squares problem and the modified residual norm steepest descent algorithm, are used for deblurring. It is shown that a 27% gain in spatial resolution can be obtained.
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