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@INPROCEEDINGS{Xu:908203,
      author       = {Xu, Hancong and Scheins, Juergen and Caldeira, Liliana and
                      Lenz, Mirjam and Ma, Bo and Lerche, Christoph and Shah, N.
                      J.},
      title        = {{R}esolution {M}odelling in {P}rojection {S}pace using
                      {F}actorized {M}ulti-block {D}etector {R}esponse {F}unction},
      reportid     = {FZJ-2022-02454},
      year         = {2018},
      abstract     = {Abstract:Position emission tomography (PET) images usually
                      suffer from low spatial resolution and signal-to-noise (SNR)
                      ratio. The degradation of image resolution in PET is caused
                      by detection process, e.g. inter-crystal scattering, crystal
                      penetration. An Accurate Detector Response Functions (DRF)
                      allows to model these phenomena and increase the spatial
                      resolution as well as SNR in the iterative image
                      reconstruction. However, fully 3D DRF for pixelated crystal
                      arrays (block) which also considers inter-block penetration
                      and inter-crystal scattering between different blocks still
                      remains challenging. Here we demonstrate the development of
                      an accurate DRF for the Siemens Hybrid MR-BrainPET system
                      with a 9-block model using GATE simulations. Different
                      incident γ rays are described by four parameters (x, y, θ,
                      φ) in Block Coordinate System. Their detection response,
                      comprising a list of fired crystals' id and corresponding
                      detection probability, are stored as an entry of a 4D
                      Look-up Table (LUT) addressed by (x, y, θ, φ). Based on
                      the DRF LUT, a PSF blurring kernel in 4D projection space
                      can be obtained by combining two multi-block DRF according
                      to the intersected block pair for each Line-of-Response. PSF
                      modelling in projection space is implemented in the
                      reconstruction toolkit PRESTO based on the developed DRF
                      LUT. A resolution phantom with 6 types of hot rods is
                      simulated by GATE and reconstructed by PRESTO with MLEM and
                      MLEM-PSF. Visual results demonstrate that with moderate
                      statistics (2.8×10 8 ), MLEM-PSF could recover small bins
                      (5 mm) at the edge of FOV in a more accurate way compared to
                      MLEM. Furthermore, the images of MLEM-PSF show better noise
                      suppression.},
      month         = {Nov},
      date          = {2018-11-10},
      organization  = {2018 IEEE Nuclear Science Symposium
                       and Medical Imaging Conference
                       (NSS/MIC), Sydney (Australia), 10 Nov
                       2018 - 17 Nov 2018},
      cin          = {INM-11 / INM-4 / JARA-BRAIN},
      cid          = {I:(DE-Juel1)INM-11-20170113 / I:(DE-Juel1)INM-4-20090406 /
                      I:(DE-Juel1)VDB1046},
      pnm          = {5253 - Neuroimaging (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5253},
      typ          = {PUB:(DE-HGF)1},
      doi          = {10.1109/NSSMIC.2018.8824424},
      url          = {https://juser.fz-juelich.de/record/908203},
}