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      Phantom and Clinical Evaluation of the Bayesian Penalized Likelihood Reconstruction Algorithm Q.Clear on an LYSO PET/CT System.

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          Abstract

          Q.Clear, a Bayesian penalized-likelihood reconstruction algorithm for PET, was recently introduced by GE Healthcare on their PET scanners to improve clinical image quality and quantification. In this work, we determined the optimum penalization factor (beta) for clinical use of Q.Clear and compared Q.Clear with standard PET reconstructions.

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          Author and article information

          Journal
          J. Nucl. Med.
          Journal of nuclear medicine : official publication, Society of Nuclear Medicine
          1535-5667
          0161-5505
          Sep 2015
          : 56
          : 9
          Affiliations
          [1 ] Department of Radiology, Churchill Hospital, Oxford University Hospitals NHS Trust, Oxford, United Kingdom Department of Oncology, University of Oxford, Old Road Campus Research Building, Oxford, United Kingdom; and eugene.teoh@oncology.ox.ac.uk.
          [2 ] Department of Oncology, University of Oxford, Old Road Campus Research Building, Oxford, United Kingdom; and Radiation Physics and Protection, Churchill Hospital, Oxford University Hospitals NHS Trust, Oxford, United Kingdom.
          [3 ] Department of Radiology, Churchill Hospital, Oxford University Hospitals NHS Trust, Oxford, United Kingdom.
          [4 ] Department of Radiology, Churchill Hospital, Oxford University Hospitals NHS Trust, Oxford, United Kingdom Department of Oncology, University of Oxford, Old Road Campus Research Building, Oxford, United Kingdom; and.
          Article
          jnumed.115.159301 EMS64174
          10.2967/jnumed.115.159301
          4558942
          26159585
          © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

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