Zoltan Domokos
ABSTRACT
In computed tomography and several related scientific domains, the Fourier slice theorem is a powerful mathematical tool to solve the problem of image reconstruction. Although this theorem is well understood in the continuous case, a detailed quantitative analysis of artifacts caused by discretization is rarely found in the computed tomographic literature. Assuming a practical Fourier Domain Reconstruction (FDR) algorithm, which performs resampling by interpolation or approximation in the frequency domain, artifacts have two main sources. One of these is a combination of truncation and aliasing, introduced by Discrete Fourier Transform (DFT), while the other is the numerical error of the function estimation algorithm that performs resampling. Here, we provide an algebraic method to quantitatively isolate distinct sources of error and construct a set of novel metrics that can be used in the numerical analysis of reconstruction methods.
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Index Terms
- Quantitative Analysis of Artificial Validation Sets for Fourier Domain CT Reconstruction
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