Zhang J, Huang H K
Department of Radiology, University of California, San Francisco 94143-0628, USA.
Comput Med Imaging Graph. 1998 Jan-Feb;22(1):31-40. doi: 10.1016/s0895-6111(98)00006-8.
Computed radiography (CR) has become a widely used imaging modality replacing the conventional screen/film procedure in diagnostic radiology. After a latent image is captured in a CR imaging plate, there are seven key processes required before a CR image can be reliably archived and displayed in a picture archiving and communication system (PACS) environment. Human error, computational bottlenecks, software bugs, and CR system errors often crash the CR acquisition and post-processing computers which results in a delay of transmitting CR images for proper viewing at the workstation. In this paper, we present a control theory and a fault tolerance algorithm, as well as their implementation in the PACS environment to circumvent such problems. The software implementation of the control theory and the algorithm is based on the event-driven, multilevel adaptive processing structure. The automated software has been used to provide real-time monitoring and control of CR image acquisition and post-processing in the intensive care unit module of the PACS operation at the University of California, San Francisco. Results demonstrate that the multilevel adaptive process control structure improves CR post-processing time, increases the reliability of the CR images delivery, minimizes user intervention, and speeds up the previously time-consuming quality assurance procedure.
计算机X线摄影(CR)已成为一种广泛应用的成像方式,在诊断放射学中取代了传统的屏/片程序。在CR成像板中捕获潜影后,在CR图像能够可靠存档并在图像存档与通信系统(PACS)环境中显示之前,需要七个关键过程。人为错误、计算瓶颈、软件漏洞和CR系统错误经常导致CR采集和后处理计算机崩溃,从而导致传输CR图像以便在工作站上进行正确查看的延迟。在本文中,我们提出了一种控制理论和一种容错算法,以及它们在PACS环境中的实现,以规避此类问题。控制理论和算法的软件实现基于事件驱动的多级自适应处理结构。该自动化软件已用于在加利福尼亚大学旧金山分校PACS操作的重症监护病房模块中对CR图像采集和后处理进行实时监测和控制。结果表明,多级自适应过程控制结构缩短了CR后处理时间,提高了CR图像传输的可靠性,最大限度地减少了用户干预,并加快了以前耗时的质量保证程序。