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Volume 28, Issue 3
Accurate Attenuation Correction for Algebraic Reconstruction Technique in SPECT

Elie Nasr

J. Comp. Math., 28 (2010), pp. 401-417.

Published online: 2010-06

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  • Abstract

We present a new iterative reconstruction algorithm to improve the algebraic reconstruction technique (ART) for the Single-Photon Emission Computed Tomography. Our method is a generalization of the Kaczmarz iterative algorithm for solving linear systems of equations and introduces exact and implicit attenuation correction derived from the attenuated Radon transform operator at each step of the algorithm. The performances of the presented algorithm have been tested upon various numerical experiments in presence of both strongly non-uniform attenuation and incomplete measurements data. We also tested the ability of our algorithm to handle moderate noisy data. Simulation studies demonstrate that the proposed method has a significant improvement in the quality of reconstructed images over ART. Moreover, convergence speed was improved and stability was established, facing noisy data, once we incorporate filtration procedure in our algorithm.

  • AMS Subject Headings

65F10, 65R32, 68U10, 92C55.

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{JCM-28-401, author = {}, title = {Accurate Attenuation Correction for Algebraic Reconstruction Technique in SPECT}, journal = {Journal of Computational Mathematics}, year = {2010}, volume = {28}, number = {3}, pages = {401--417}, abstract = {

We present a new iterative reconstruction algorithm to improve the algebraic reconstruction technique (ART) for the Single-Photon Emission Computed Tomography. Our method is a generalization of the Kaczmarz iterative algorithm for solving linear systems of equations and introduces exact and implicit attenuation correction derived from the attenuated Radon transform operator at each step of the algorithm. The performances of the presented algorithm have been tested upon various numerical experiments in presence of both strongly non-uniform attenuation and incomplete measurements data. We also tested the ability of our algorithm to handle moderate noisy data. Simulation studies demonstrate that the proposed method has a significant improvement in the quality of reconstructed images over ART. Moreover, convergence speed was improved and stability was established, facing noisy data, once we incorporate filtration procedure in our algorithm.

}, issn = {1991-7139}, doi = {https://doi.org/10.4208/jcm.2009.10-m2873}, url = {http://global-sci.org/intro/article_detail/jcm/8527.html} }
TY - JOUR T1 - Accurate Attenuation Correction for Algebraic Reconstruction Technique in SPECT JO - Journal of Computational Mathematics VL - 3 SP - 401 EP - 417 PY - 2010 DA - 2010/06 SN - 28 DO - http://doi.org/10.4208/jcm.2009.10-m2873 UR - https://global-sci.org/intro/article_detail/jcm/8527.html KW - Single-photon emission computed tomography, Attenuated radon transform, Algebraic reconstruction technique, Attenuation correction. AB -

We present a new iterative reconstruction algorithm to improve the algebraic reconstruction technique (ART) for the Single-Photon Emission Computed Tomography. Our method is a generalization of the Kaczmarz iterative algorithm for solving linear systems of equations and introduces exact and implicit attenuation correction derived from the attenuated Radon transform operator at each step of the algorithm. The performances of the presented algorithm have been tested upon various numerical experiments in presence of both strongly non-uniform attenuation and incomplete measurements data. We also tested the ability of our algorithm to handle moderate noisy data. Simulation studies demonstrate that the proposed method has a significant improvement in the quality of reconstructed images over ART. Moreover, convergence speed was improved and stability was established, facing noisy data, once we incorporate filtration procedure in our algorithm.

Elie Nasr. (2019). Accurate Attenuation Correction for Algebraic Reconstruction Technique in SPECT. Journal of Computational Mathematics. 28 (3). 401-417. doi:10.4208/jcm.2009.10-m2873
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