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@ARTICLE{Hahn:130786,
      author       = {J. Hahn$^*$ and H. Bruder$^*$ and C. Rohkohl$^*$ and T.
                      Allmendinger and K. Stierstorfer and T. Flohr and M.
                      Kachelriess$^*$},
      title        = {{M}otion compensation in the region of the coronary
                      arteries based on partial angle reconstructions from
                      short-scan {CT} data.},
      journal      = {Medical physics},
      volume       = {44},
      number       = {11},
      issn         = {0094-2405},
      address      = {New York, NY},
      reportid     = {DKFZ-2017-05864},
      pages        = {5795 - 5813},
      year         = {2017},
      abstract     = {In order to mitigate motion-induced artifacts, several
                      motion compensation (MoCo) methods have been developed,
                      which are either able to (a) compensate for severe
                      artifacts, but utilize the data for the reconstruction of
                      several cardiac phases, or (b) improve image quality of a
                      single reconstruction with only moderate motion artifacts.
                      We propose a method combining both benefits: dose efficiency
                      by utilizing only the data needed for a single short-scan
                      reconstruction while still being able to compensate for
                      severe artifacts.We introduce a MoCo method, which we call
                      PAMoCo, to improve the visualization of the coronary
                      arteries of a standard coronary CT angiography exam by
                      reducing motion artifacts. As a first step, we segment a
                      region of interest covering a chosen coronary artery. We
                      subdivide a volume covering the whole heart into several
                      stacks, which are sub-volumes, reconstructed from
                      phase-correlated short-scan data acquired during different
                      heart cycles. Motion-compensated reconstruction is performed
                      for each stack separately, based on partial angle
                      reconstructions, which are derived by dividing the data
                      corresponding to the segmented stack volume into several
                      double-overlapping sectors. We model motion along the
                      coronary artery center line obtained from segmentation and
                      the temporal dimension by a low-degree polynomial and create
                      a dense 3D motion vector field (MVF). The parameters
                      defining the MVF are estimated by optimizing an image
                      artifact measuring cost function and we employ a semi-global
                      optimization routine by re-initializing the optimization
                      multiple times. The algorithm was evaluated on the basis of
                      a phantom measurement and clinical data. For the phantom
                      measurement an artificial vessel equipped with calcified
                      lesions mounted on a moving robot arm was measured, where
                      typical coronary artery motion patterns for 70 bpm and 90
                      bpm have been applied. For analysis, we calculated the
                      calcified volume V inside an ROI and measured the maximum
                      vessel diameter d based on cross-sectional views to compare
                      the performances of standard reconstructions obtained via
                      filtered backprojection (FBP) and PAMoCo reconstructions
                      between $20\%$ and $80\%$ of the cardiac cycle. Further, the
                      new algorithm was applied to six clinical cases of patients
                      with heart rates between 50 bpm and 74 bpm. Standard FBP,
                      PAMoCo reconstructions were performed and compared to best
                      phase FBP reconstructions and another MoCo algorithm, which
                      is based on motion artifact metrics (MAM), via visual
                      inspection.In case of the phantom measurement we found a
                      strong dependence of V and d on the cardiac phase in case of
                      the FBP reconstructions. When applying PAMoCo, V and d
                      became almost constant due to a better discrimination from
                      calcium to vessel and water background and values close to
                      the ground truth have been derived. In the clinical study we
                      chose reconstructions showing strong motion artifacts and
                      observed a substantially improved delineation of the
                      coronary arteries in PAMoCo reconstructions compared to the
                      standard FBP reconstructions and also the MAM images,
                      confirming the findings of the phantom measurement.Due to
                      the fast reconstruction of PAMoCo images and the
                      introduction of a new motion model, we were able to
                      re-initialize the optimization routine at pre-selected
                      parameter sets and thereby increase the potential of the MAM
                      algorithm. From the phantom measurement we conclude that
                      PAMoCo performed almost equally well in all cardiac phases
                      and suggest applying the PAMoCo algorithm for single source
                      systems in case of patients with high or irregular heart
                      rates.},
      cin          = {E020 / E025},
      ddc          = {610},
      cid          = {I:(DE-He78)E020-20160331 / I:(DE-He78)E025-20160331},
      pnm          = {315 - Imaging and radiooncology (POF3-315)},
      pid          = {G:(DE-HGF)POF3-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:28801918},
      doi          = {10.1002/mp.12514},
      url          = {https://inrepo02.dkfz.de/record/130786},
}