Fast kernel-based reconstruction from spherical mean data

Authors

Thomas Wiatowski

Reference

Applied Inverse Problems Conference, Daejeon, South Korea, July 2013, (invited talk).

Abstract

The reconstruction of images from data modeled by the spherical Radon transform plays an important role in photoacoustic tomography - a rapidly developing modality for in vivo imaging. We provide a novel kernel-based reconstruction algorithm adapted to this type of data. We propose a discretization of the spherical Radon transform that allows us to employ fast Fourier transform techniques and so to obtain a fast and memory efficient algorithm, and demonstrate the applicability of our method in numerical experiments on real and synthetic data.

Keywords

Radial basis functions, algebraic reconstruction, spherical Radon transform, fast Fourier transform techniques, photoacoustic tomography.

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