Literature DB >> 16598644

Predicting clinical image delivery time by monitoring PACS queue behavior.

Nelson E King1, Jorge Documet, Brent Liu.   

Abstract

The expectation of rapid image retrieval from PACS users contributes to increased information technology (IT) infrastructure investments to increase performance as well as continuing demands upon PACS administrators to respond to "slow" system performance. The ability to provide predicted delivery times to a PACS user may curb user expectations for "fastest" response especially during peak hours. This, in turn, could result in a PACS infrastructure tailored to more realistic performance demands. A PACS with a stand-alone architecture under peak load typically holds study requests in a queue until the DICOM C-Move command can take place. We investigate the contents of a stand-alone architecture PACS RetrieveSend queue and identified parameters and behaviors that enable a more accurate prediction of delivery time. A prediction algorithm for studies delayed in a stand-alone PACS queue can be extendible to other potential bottlenecks such as long-term storage archives. Implications of a queue monitor in other PACS architectures are also discussed.

Mesh:

Year:  2006        PMID: 16598644      PMCID: PMC3045171          DOI: 10.1007/s10278-006-0262-z

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  4 in total

Review 1.  New direction in PACS education and training.

Authors:  Maria Y Y Law; Zheng Zhou
Journal:  Comput Med Imaging Graph       Date:  2003       Impact factor: 4.790

2.  PACSPulse: a web-based DICOM network traffic monitor and analysis tool.

Authors:  Paul G Nagy; Mark Daly; Max Warnock; Kevin C Ehlers; Jeff Rehm
Journal:  Radiographics       Date:  2003 May-Jun       Impact factor: 5.333

3.  Utilizing data grid architecture for the backup and recovery of clinical image data.

Authors:  Brent J Liu; M Z Zhou; J Documet
Journal:  Comput Med Imaging Graph       Date:  2005-01-11       Impact factor: 4.790

4.  An XML Gateway to Patient Data for Medical Research Applications.

Authors:  Alex A T Bui; Gregory S Weinger; Susan J Barretta; John David N Dionisio; Hooshang Kangarloo
Journal:  Ann N Y Acad Sci       Date:  2002-12       Impact factor: 5.691

  4 in total
  1 in total

1.  A filmless radiology department in a full digital regional hospital: quantitative evaluation of the increased quality and efficiency.

Authors:  Andrea Nitrosi; Giovanni Borasi; Franco Nicoli; Gino Modigliani; Andrea Botti; Marco Bertolini; Pietro Notari
Journal:  J Digit Imaging       Date:  2007-02-23       Impact factor: 4.056

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.