Two-dimensional water temperature reconstruction by filtered back-projection method

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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Monte Carlo evaluation of the Filtered Back Projection method for image reconstruction in proton computed tomography

Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment ◽

10.1016/j.nima.2011.05.061 ◽

2011 ◽

Vol 658 (1) ◽

pp. 78-83 ◽

Cited By ~ 22

Author(s):

G.A.P. Cirrone ◽

M. Bucciolini ◽

M. Bruzzi ◽

G. Candiano ◽

C. Civinini ◽

...

Keyword(s):

Computed Tomography ◽

Monte Carlo ◽

Image Reconstruction ◽

Projection Method ◽

Back Projection ◽

Filtered Back Projection ◽

Proton Computed Tomography ◽

Monte Carlo Evaluation

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Imaging in turbid media by modified filtered back projection method using data from Monte Carlo simulation

10.1117/12.484108 ◽

2003 ◽

Author(s):

Ashwani Aggarwal ◽

Ram M. Vasu

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Projection Method ◽

Turbid Media ◽

Back Projection ◽

Filtered Back Projection ◽

Using Data

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Investigation of the quantitative accuracy of 3D iterative reconstruction algorithms in comparison to filtered back projection method: a phantom study

10.1117/12.2043586 ◽

2014 ◽

Author(s):

Nouf Abuhadi ◽

David Bradley ◽

Dev Katarey ◽

Zsolt Podolyak ◽

Salem Sassi

Keyword(s):

Projection Method ◽

Iterative Reconstruction ◽

Phantom Study ◽

Back Projection ◽

Reconstruction Algorithms ◽

Filtered Back Projection ◽

Quantitative Accuracy

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Regularized Iterative Weighted Filtered Back-Projection for Few-View Data Photoacoustic Imaging

Computational and Mathematical Methods in Medicine ◽

10.1155/2016/9732142 ◽

2016 ◽

Vol 2016 ◽

pp. 1-8

Author(s):

Xueyan Liu ◽

Dong Peng

Keyword(s):

Projection Method ◽

Photoacoustic Imaging ◽

Evaluation Studies ◽

Back Projection ◽

Filtered Back Projection ◽

Streak Artifacts ◽

Wide Range ◽

Quantitative Image ◽

Noninvasive Imaging Technique ◽

Robustness To Noise

Photoacoustic imaging is an emerging noninvasive imaging technique with great potential for a wide range of biomedical imaging applications. However, with few-view data the filtered back-projection method will create streak artifacts. In this study, the regularized iterative weighted filtered back-projection method was applied to our photoacoustic imaging of the optical absorption in phantom from few-view data. This method is based on iterative application of a nonexact 2DFBP. By adding a regularization operation in the iterative loop, the streak artifacts have been reduced to a great extent and the convergence properties of the iterative scheme have been improved. Results of numerical simulations demonstrated that the proposed method was superior to the iterative FBP method in terms of both accuracy and robustness to noise. The quantitative image evaluation studies have shown that the proposed method outperforms conventional iterative methods.

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