Two-dimensional noise reconstruction in proton computed tomography using distance-driven filtered back-projection of simulated projections

2018 ◽  
Vol 63 (21) ◽  
pp. 215009 ◽  
Author(s):  
Martin Rädler ◽  
Guillaume Landry ◽  
Simon Rit ◽  
Reinhard W Schulte ◽  
Katia Parodi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Two Dimensional ◽  
Back Projection ◽  
Filtered Back Projection ◽  
Proton Computed Tomography

A reconstruction algorithm for coherent scatter computed tomography based on filtered back-projection

2003 ◽  
Vol 30 (9) ◽  
pp. 2465-2474 ◽  
Author(s):  
U. van Stevendaal ◽  
J.-P. Schlomka ◽  
A. Harding ◽  
M. Grass
Keyword(s):  
Computed Tomography ◽  
Reconstruction Algorithm ◽  
Back Projection ◽  
Filtered Back Projection ◽  
Coherent Scatter

scholarly journals Suppression of Cone-Beam Artefacts with Direct Iterative Reconstruction Computed Tomography Trajectories (DIRECTT)

2021 ◽  
Vol 7 (8) ◽  
pp. 147
Author(s):  
Sotirios Magkos ◽  
Andreas Kupsch ◽  
Giovanni Bruno
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Iterative Reconstruction ◽  
Cone Beam ◽  
Back Projection ◽  
Projection Algorithms ◽  
Filtered Back Projection ◽  
Tomography Data

The reconstruction of cone-beam computed tomography data using filtered back-projection algorithms unavoidably results in severe artefacts. We describe how the Direct Iterative Reconstruction of Computed Tomography Trajectories (DIRECTT) algorithm can be combined with a model of the artefacts for the reconstruction of such data. The implementation of DIRECTT results in reconstructed volumes of superior quality compared to the conventional algorithms.

What Else for Improvement of Reconstructed Densities?

2010 ◽  
Vol 666 ◽  
pp. 147-150
Author(s):  
M. Biasini ◽  
G. Kontrym-Sznajd
Keyword(s):  
Angular Correlation ◽  
Series Expansion ◽  
Real Data ◽  
Annihilation Radiation ◽  
Two Dimensional ◽  
Back Projection ◽  
Filtered Back Projection ◽  
Transform Methods ◽  
Experimental Noise ◽  
Algebraic Technique

Reconstruction techniques, belonging to two different categories (series expansion and transform methods), are compared with regard to their applicability to line projections of a model density. It is demonstrated that in the case of this model the algebraic technique gives much better results than the filtered back projection (FBP) algorithm. However, it could not be a case for real data where a region of densities to be considered is very large comparing to the modelled one. In this connection we propose a new way of dealing with two-dimensional (2D) angular correlation of annihilation radiation (ACAR) data. Such a treatment, proposed for all reconstruction techniques, allows to improve reconstructed densities and filters the experimental noise.

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