Making the PACS workstation a browser of image processing software: a feasibility study using inter-process communication techniques

Original Article

Abstract

Purpose

To enhance the functional expandability of a picture archiving and communication systems (PACS) workstation and to facilitate the integration of third-part image-processing modules, we propose a browser–server style method.

Methods

In the proposed solution, the PACS workstation shows the front-end user interface defined in an XML file while the image processing software is running in the background as a server. Inter-process communication (IPC) techniques allow an efficient exchange of image data, parameters, and user input between the PACS workstation and stand-alone image-processing software. Using a predefined communication protocol, the PACS workstation developer or image processing software developer does not need detailed information about the other system, but will still be able to achieve seamless integration between the two systems and the IPC procedure is totally transparent to the final user.

Results

A browser–server style solution was built between OsiriX (PACS workstation software) and MeVisLab (Image-Processing Software). Ten example image-processing modules were easily added to OsiriX by converting existing MeVisLab image processing networks. Image data transfer using shared memory added <10 ms of processing time while the other IPC methods cost 1–5 s in our experiments.

Conclusion

The browser–server style communication based on IPC techniques is an appealing method that allows PACS workstation developers and image processing software developers to cooperate while focusing on different interests.

Keywords

PACS workstation Image processing Functional expandability Client–server communication Inter-process communication 

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References

  1. 1.
    Ratib O (2009) Imaging informatics: from image management to image navigation. Yearb Med Inform 167–172Google Scholar
  2. 2.
    MeVisLab. Medical image processing and visualization. http://www.mevislab.de/
  3. 3.
    3D Slicer. http://slicer.org/
  4. 4.
    Toussaint N, Souplet J, Fillard P (2007) MedINRIA: medical image navigation and research tool by INRIA. In: Proceedings of MICCAI’07 workshop on interaction in medical image analysis and visualizationGoogle Scholar
  5. 5.
    Rosset A, Spadola L, Ratib O (2004) OsiriX: an open-source software for navigating in multidimensional DICOM images. J Digit Imaging 17: 205–216CrossRefPubMedGoogle Scholar
  6. 6.
    MeVis Medical Solution AG (2009) Getting started: first steps with MeVisLab. http://www.mevislab.de/developer/documentation/
  7. 7.
  8. 8.
    Stevens WR (1998) UNIX network programming. Interprocess communications, vol 2, 2nd edn. Prentice-Hall, Englewood CliffsGoogle Scholar
  9. 9.
  10. 10.
    Wang C, Frimmel H, Persson A, Smedby Ö (2008) An interactive software module for visualizing coronary arteries in CT angiography. Int J Comput Assist Radiol Surg 3: 11–18CrossRefGoogle Scholar
  11. 11.
    Fisichella VA, Jäderling F, Horvath S, Stotzer P, Kilander A, Båth M, Hellström M (2009) Computer-aided detection (CAD) as a second reader using perspective filet view at CT colonography: effect on performance of inexperienced readers. Clin Radiol 64: 972–982CrossRefPubMedGoogle Scholar
  12. 12.
    Knöss N, Hoffmann B, Fabel M, Wiese C, Jochens A, Bolte H, Heller M, Biederer J (2009) Lung nodule assessment in computed tomography: precision of attenuation measurement based on computer-aided volumetry. Rofo 181: 1151–1156PubMedGoogle Scholar
  13. 13.
    Sörstedt E, Persson A, Noren B, Björnlert U, Malcherek P, Axelsson M, Johansson J, Smedby Ö (2005) Computed tomo- graphic colonography: comparison of two workstations. Acta Radiol 46: 671–678CrossRefPubMedGoogle Scholar
  14. 14.
    Dikkers R, Willems TP, de Jonge GJ, Marquering HA, Greuter MJW, van Ooijen PMA, van der Weide MCJ, Oudkerk M (2009) Accuracy of noninvasive coronary stenosis quantification of different commercially available dedicated software packages. J Comput Assist Tomogr 33: 505–512CrossRefPubMedGoogle Scholar

Copyright information

© CARS 2010

Authors and Affiliations

  1. 1.Department of Radiology (IMH)Linköping UniversityLinköpingSweden
  2. 2.Center for Medical Image Science and Visualization (CMIV)Linköping University Hospital, Linköping UniversityLinköpingSweden
  3. 3.Fraunhofer MEVIS, Institute for Medical Image ComputingBremenGermany

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