Proc. SPIE. 8674, Medical Imaging 2013: Advanced PACS-based Imaging Informatics and Therapeutic Applications
KEYWORDS: Switches, Medicine, Atrial fibrillation, Particles, Computing systems, Computer simulations, Monte Carlo methods, Operating systems, Parallel computing, Picture Archiving and Communication System
The Monte Carlo (MC) technique has been widely used as the gold standard for interaction of radiation with matter in the fields of medical physics, radiation therapy, and nuclear medicine. However, MC simulation is time consuming and requires a lot of computational resources. Generally, a dedicated high performance computing cluster is use to improve efficiency, but it is costly and lacks of the ability to run routine errands in healthcare facilities. In this study, we proposed a method for rapid deployment of computing platform for MC simulation in the PACS environment using review workstations as computing nodes. The workstations were booted from the network and initialed a RAM disk as the boot sector. The simplified Linux operating system and the Monte Carlo N-Particle Transport Code Version 5 (MCNP5) were transferred from the DRBL (Diskless Remote Boot in Linux) server to each node automatically. The cluster computing environment can be established within four minutes. We compared a commercially available dedicated cluster with the DRBL cluster. The results showed that the commercial cluster had a slightly higher acceleration factor than the DRBL cluster. The simulation time of the commercial and the DRBL clusters for 2×10<sup>8</sup> particle histories was 37,151 and 40,021 sec, respectively. When the number of rendezvous increased to 20, the maximum time differences between both clusters were 95 and 85 sec for the megabit and the gigabit switches. We conclude that the DRBL cluster can be quickly deployed to the non-workloaded review workstations in the PACS. Thus, the MC technique could be broadly used to enhance the research capability of radiological sciences in healthcare facilities.
Urban heat island (UHI) effect can be characterized by increasing surface and atmospheric temperature and decreasing
rainfall amount in urban area. This research detected the impact of urban land use changes to UHI effect in Taichung city
at Taiwan by temporal ASTER and MODIS satellite images and measured data from ground thermometer stations. From
spatially analyzed data output, the results showed a linear pattern between land use changes to UHI effect for study area.