Proceedings Article | 1 May 1996
KEYWORDS: Picture Archiving and Communication System, Data acquisition, Computed tomography, Image retrieval, Telecommunications, Computing systems, Data storage, Image acquisition, Image storage, Chromium
This paper describes the current status of the second generation PACS at UCSF commenced in October 1992. The UCSF PACS is designed in-house as a hospital-integrated PACS based on an open architecture concept using industrial standards including UNIX operating system, C programming language, X-Window user interface, TCP/IP communication protocol, DICOM 3.0 image standard and HL7 health data format. Other manufacturer's PACS components which conform with these standards can be easily integrated into the system. Relevant data from HIS and RIS is automatically incorporated into the PACS using HL7 data format and TCP/IP communication protocol. The UCSF system also takes advantage of state-of-the-art communication, storage, and software technologies in ATM, multiple storage media, automatic programming, multilevel processes for a better cost-performance system. The primary PACS network is the 155 Mbits/sec OC3 ATM with the Ethernet as the back-up. The UCSF PACS also connects Mt. Zion Hospital and San Francisco VA Medical Center in the San Francisco Bay area via an ATM wide area network with a T1 line as the back-up. Currently, five MR and five CT scanners from multiple sites, two computed radiography systems, two film digitizers, one US PACS module, the hospital HIS and the department RIS have been connected to the PACS network. The image data is managed by a mirrored database (Sybase). The PACS controller, with its 1.3 terabyte optical disk library, acquires 2.5 gigabytes digital data daily. Four 2K, five, 1,600-line multiple monitor display workstations are on line in neuroradiology, pediatric radiology and intensive care units for clinical use. In addition, the PACS supports over 100 Macintosh users in the department and selected hospital sites for both images and textual retrieval through a client/server mechanism. We are also developing a computation and visualization node in the PACS network for advancing radiology research.
