High End Computing for PET/SPECT

描述（由申请人提供）：用于脑和其他器官的高分辨率PET成像继续经历巨大的技术进步。一个例子是最近在约翰霍普金斯大学的NIH SIG 1 S10 RR 017219 - 01 A1的赞助下安装的高分辨率研究断层扫描仪（HRRT），其是分辨率和灵敏度最高的人脑专用扫描仪。当前重建软件和潜在替代方案的计算需求具有挑战性，但可行。我们要求计算机硬件支持几个NIH资助的项目，采用发射断层扫描（PET/SPECT）。部分是将我们目前的32个节点集群大小增加一倍，分配给HRT常规重建，这将大大提高吞吐量，而不会牺牲大量（超过26个）动物和临床协议的定量准确性。随着我们的NIH研究从其他NIH NCRR支持的扫描仪转移，这些需求将变得更大，并且GE Advance变得过时（现在已有8年历史）。其次，一些NIH项目需要更多的计算时间。这包括进一步改进HRRT定量，包括头部移动校正（HRRT有超过207个切片）和适当的校正，包括扫描仪等，并且使用基于Linux的程序的更精确的重建需要在仅开发集群上的并行工作。此外，需要4个NIH SPECT/PET项目，包括密集的模拟和SPECT重建。因此，我们要求将其增加到24节点群集。这也将包括由在心脏和癌症中研究类似算法的合作者进行的算法开发。所有这些项目都得到了总共30个NIH资助的、待定的或试点的研究的支持，这些研究需要这些计算设施来进行人类、动物或计算断层扫描研究。通过提供这种额外的设备，这将允许充分利用已经资助的NCRR PET扫描仪，同时继续进行基础和应用脑和其他NIH相关研究，并将这种高分辨率扫描的限制扩展到以前没有实现的应用中。

DESCRIPTION (provided by applicant): High resolution PET imaging for Brain and other organs continues to undergo enormous technological advances. One example is the High Resolution Research Tomograph (HRRT) the highest resolution and sensitivity human brain dedicated scanner which was recently installed under the auspices of an NIH SIG, 1S10RR017219-01A1, at Johns Hopkins University. The computational demands for the current reconstruction software and potential alternative are challenging but feasible. We are requesting the computer hardware to support several NIH funded projects employing emission tomography (PET/SPECT). Part is to double our current 32 node cluster size, allocated for HRRT routine reconstruction, which will substantially improve throughput without sacrificing quantitative accuracy for the large number (over 26) of animal and clinical protocols to be supported. These demands will become even greater as our NIH research studies shift from the other NIH NCRR supported scanner, and the GE Advance becomes obsolete (now 8 years old). Secondly, a number of NIH projects require more computational time. This includes further improvements in HRRT quantitation including head movement correction (the HRRT has over 207 slices) and appropriate corrections including scanner, etc., and more accurate reconstructions using Linux based program require a parallel effort on a development only cluster. Furthermore, 4 NIH SPECT/PET projects involving intensive simulations and SPECT reconstructions are needed. Hence we are requesting increasing this to a 24 node cluster. This will also incorporate algorithm development by collaborators working on similar algorithms in heart and cancer. All of these projects are supported by a total of 30 NIH funded, pending or pilot studies needing these computing facilities for human, animal or calculation tomography research. By providing this additional equipment this will allow full utilization of an already funded NCRR PET scanner while continued work by both basic as well as applied brain and other NIH related research and extend the limits of this high resolution scanning into applications not realized before.