@article{TEXTUAL,
      recid = {8380},
      author = {Chou, Cheng-Ying and Dong, Yun and Hung, Yukai and Kao,  Yu-Jiun and Wang, Weichung and Kao, Chien-Min and Chen,  Chin-Tu},
      title = {Accelerating Image Reconstruction in Dual-Head PET System  by GPU and Symmetry Properties},
      journal = {PLOS ONE},
      address = {2012-12-26},
      number = {TEXTUAL},
      abstract = {<p>Positron emission tomography (PET) is an important  imaging modality in both clinical usage and research  studies. We have developed a compact high-sensitivity PET  system that consisted of two large-area panel PET detector  heads, which produce more than 224 million lines of  response and thus request dramatic computational demands.  In this work, we employed a state-of-the-art graphics  processing unit (GPU), NVIDIA Tesla C2070, to yield an  efficient reconstruction process. Our approaches  ingeniously integrate the distinguished features of the  symmetry properties of the imaging system and GPU  architectures, including block/warp/thread assignments and  effective memory usage, to accelerate the computations for  ordered subset expectation maximization (OSEM) image  reconstruction. The OSEM reconstruction algorithms were  implemented employing both CPU-based and GPU-based codes,  and their computational performance was quantitatively  analyzed and compared. The results showed that the  GPU-accelerated scheme can drastically reduce the  reconstruction time and thus can largely expand the  applicability of the dual-head PET system.</p>},
      url = {http://knowledge.uchicago.edu/record/8380},
}