<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The paper presented here describes a new practical approach to the reconstruction problem applied to 3D spiral x-ray tomography. The concept we propose is based on a continuous-to-continuous data model, and the reconstruction problem is formulated as a shift invariant system. This original reconstruction method is formulated taking into consideration the statistical properties of signals obtained by the 3D geometry of a CT scanner. It belongs to the class of nutating reconstruction methods and is based on the advanced single slice rebinning (ASSR) methodology. The concept shown here significantly improves the quality of the images obtained after reconstruction and decreases the complexity of the reconstruction problem in comparison with other approaches. Computer simulations have been performed, which prove that the reconstruction algorithm described here does indeed significantly outperforms conventional analytical methods in the quality of the images obtained.</p></abstract>

The paper presented here describes a new practical approach to the reconstruction problem applied to 3D spiral x-ray tomography. The concept we propose is based on a continuous-to-continuous data model, and the reconstruction problem is formulated as a shift invariant system. This original reconstruction method is formulated taking into consideration the statistical properties of signals obtained by the 3D geometry of a CT scanner. It belongs to the class of nutating reconstruction methods and is based on the advanced single slice rebinning (ASSR) methodology. The concept shown here significantly improves the quality of the images obtained after reconstruction and decreases the complexity of the reconstruction problem in comparison with other approaches. Computer simulations have been performed, which prove that the reconstruction algorithm described here does indeed significantly outperforms conventional analytical methods in the quality of the images obtained.

A Practical Statistical Approach to the Reconstruction Problem Using a Single Slice Rebinning Method

Journal of Artificial Intelligence and Soft Computing Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The paper presented here describes a new practical approach to the reconstruction problem applied to 3D spiral x-ray tomography. The concept we propose is...

A Practical Statistical Approach to the Reconstruction Problem Using a Single Slice Rebinning Method

Publié en ligne: 20 mars 2020

Pages: 137 - 149

Reçu: 11 sept. 2019

Accepté: 05 mars 2020

DOI: https://doi.org/10.2478/jaiscr-2020-0010

Mots clés
reconstruction algorithm, statistical iterative method, computed tomography

© 2020 Robert Cierniak et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

A Practical Statistical Approach to the Reconstruction Problem Using a Single Slice Rebinning Method

Publié en ligne: 20 mars 2020

Pages: 137 - 149

Reçu: 11 sept. 2019

Accepté: 05 mars 2020

DOI: https://doi.org/10.2478/jaiscr-2020-0010

Mots clésreconstruction algorithm, statistical iterative method, computed tomography

© 2020 Robert Cierniak et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Mots clés
reconstruction algorithm, statistical iterative method, computed tomography