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      Model-based correction for scatter and tailing effects in simultaneous99mTc and123I imaging for a CdZnTe cardiac SPECT camera

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          Abstract

          An advantage of semiconductor-based dedicated cardiac single photon emission computed tomography (SPECT) cameras when compared to conventional Anger cameras is superior energy resolution. This provides the potential for improved separation of the photopeaks in dual radionuclide imaging, such as combined use of (99m)Tc and (123)I . There is, however, the added complexity of tailing effects in the detectors that must be accounted for. In this paper we present a model-based correction algorithm which extracts the useful primary counts of (99m)Tc and (123)I from projection data. Equations describing the in-patient scatter and tailing effects in the detectors are iteratively solved for both radionuclides simultaneously using a maximum a posteriori probability algorithm with one-step-late evaluation. Energy window-dependent parameters for the equations describing in-patient scatter are estimated using Monte Carlo simulations. Parameters for the equations describing tailing effects are estimated using virtually scatter-free experimental measurements on a dedicated cardiac SPECT camera with CdZnTe-detectors. When applied to a phantom study with both (99m)Tc and (123)I, results show that the estimated spatial distribution of events from (99m)Tc in the (99m)Tc photopeak energy window is very similar to that measured in a single (99m)Tc phantom study. The extracted images of primary events display increased cold lesion contrasts for both (99m)Tc and (123)I.

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          Author and article information

          Journal
          Physics in Medicine and Biology
          Phys. Med. Biol.
          IOP Publishing
          0031-9155
          1361-6560
          April 21 2015
          April 21 2015
          March 24 2015
          : 60
          : 8
          : 3045-3063
          Article
          10.1088/0031-9155/60/8/3045
          25803643
          38ae2f5d-8d4f-43bd-86b6-f3505f1f8e12
          © 2015

          http://iopscience.iop.org/info/page/text-and-data-mining

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