@misc{oai:repo.qst.go.jp:00070317,
 author = {Kinouchi, Shoko and Yamaya, Taiga and Yoshida, Eiji and Tashima, Hideaki and Kudo, Hiroyuki and Suga, Mikio and 木内 尚子 and 山谷 泰賀 and 吉田 英治 and 田島 英朗 and 工藤 博幸 and 菅 幹生},
 month = {Nov},
 note = {The OpenPET, which have a physically opened space between two detector rings, is our new geometry to enable PET imaging during radiation therapy. Especially, tracking a moving target such as a tumor in the lung will become possible if the real-time imaging system is realized. In this paper, therefore, we developed a list-mode image reconstruction method using general purpose graphic processing units (GPGPUs). We used the list-mode dynamic row-action maximum likelihood algorithm (DRAMA) with new relaxation parameter calculated by the vector of image update. For GPU implementation, the efficiency of acceleration depends on the implementation method which is required to avoid conditional statements and to use efficient memory accesses. We developed a system model in which each element of system matrix is calculated as the value of detector response function (DRF) of the length between the center of a voxel and a line of response (LOR). The system model was suited to GPU implementations that enable us to calculate each element of the system matrix with reduced number of the conditional statements. We applied the developed method to a small OpenPET prototype, which was developed for a proof-of-concept. We measured the micro-Derenzo phantom placed at the gap. The results showed that the same quality of reconstructed images using GPU as using CPU were achieved, and calculation speed on the GPU was 35.5 times faster than that on the CPU., 2010 Nuclear Science Symposium and Medical Imaging Conference},
 title = {GPU Implementation of List-mode DRAMA for Real-time OpenPET Image Reconstruction},
 year = {2010}
}