Anatomy of an Extensible Open Source PACS

Abstract

The conception and deployment of cost effective Picture Archiving and Communication Systems (PACS) is a concern for small to medium medical imaging facilities, research environments, and developing countries’ healthcare institutions. Financial constraints and the specificity of these scenarios contribute to a low adoption rate of PACS in those environments. Furthermore, with the advent of ubiquitous computing and new initiatives to improve healthcare information technologies and data sharing, such as IHE and XDS-i, a PACS must adapt quickly to changes. This paper describes Dicoogle, a software framework that enables developers and researchers to quickly prototype and deploy new functionality taking advantage of the embedded Digital Imaging and Communications in Medicine (DICOM) services. This full-fledged implementation of a PACS archive is very amenable to extension due to its plugin-based architecture and out-of-the-box functionality, which enables the exploration of large DICOM datasets and associated metadata. These characteristics make the proposed solution very interesting for prototyping, experimentation, and bridging functionality with deployed applications. Besides being an advanced mechanism for data discovery and retrieval based on DICOM object indexing, it enables the detection of inconsistencies in an institution’s data and processes. Several use cases have benefited from this approach such as radiation dosage monitoring, Content-Based Image Retrieval (CBIR), and the use of the framework as support for classes targeting software engineering for clinical contexts.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

References

  1. 1.

    Huang HK: PACS and imaging informatics: basic principles and applications. Hoboken, NJ:Wiley, p 704, 2004

  2. 2.

    Oosterwijk H: Dicom basics, third edition, aubrey. OTech, Inc, TX, 2005

    Google Scholar 

  3. 3.

    Costa C, Silva A, Oliveira J: Current perspectives on PACS and a cardiology case study. Advanced Computational Intelligence Paradigms in Healthcare. Springer Berlin, Heidelberg, pp 79–108, 2007

  4. 4.

    Duncan LD, Gray K, Lewis JM, Bell JL, Bigge J, McKinney JM: Clinical integration of picture archiving and communication systems with pathology and hospital information system in oncology. Am Surg 76:982–986, 2010

    PubMed  Google Scholar 

  5. 5.

    Ratib O, Rosset A: Open-source software in medical imaging: development of OsiriX. Int J Comput Assist Radiol Surg 1:187–196, 2006

    Article  Google Scholar 

  6. 6.

    Costa C, Ferreira C, Bastião L, Ribeiro L, Silva A, Oliveira JL: Dicoogle-an open source peer-to-peer PACS. Journal of Digit imaging 24(5):848–856, 2011

  7. 7.

    McDonald CJ, et al: Open Source software in medical informatics—why, how and what. Int J Med Inform 69:175–184, 2003

    Article  PubMed  Google Scholar 

  8. 8.

    Mansoori B, Erhard KK, Sunshine JL: Picture Archiving and Communication System (PACS) implementation, integration benefits in an Integrated Health System. Acad Radiol 19:229–235, 2012

    Article  PubMed  Google Scholar 

  9. 9.

    Myers B: U.S. Medical imaging informatics industry reconnects with growth in the enterprise image archiving market

  10. 10.

    Vossberg M, Tolxdorff T, Krefting D: DICOM image communication in Globus-based medical grids. IEEE Trans Inf Technol Biomed 12:145–153, 2008

    Article  PubMed  Google Scholar 

  11. 11.

    Yang C-T, Chen C-H, Yang M-F: Implementation of a medical image file accessing system in co-allocation data grids. Futur Gener Comput Syst 26:1127–1140, 2010

    Article  Google Scholar 

  12. 12.

    Teng CC, Mitchell J, Walker C, Swan A, Davila C, Howard D, Needham T: A medical image archive solution in the cloud. In Software Engineering and Service Sciences (ICSESS), 2010 I.E. International Conference on (pp. 431–434). IEEE, (2010, July)

  13. 13.

    Costa C, Freitas F, Pereira M, Silva A: Oliveira JeL: indexing and retrieving DICOM data in disperse and unstructured archives. Int J Comput Assist Radiol Surg 4:71–77, 2009

    Article  PubMed  Google Scholar 

  14. 14.

    Pohjonen H, Ross P, Blickman JG, Kamman R: Pervasive access to images and data—the use of computing grids and mobile/wireless devices across healthcare enterprises. IEEE Trans Inf Technol Biomed 11:81–86, 2007

    Article  PubMed  Google Scholar 

  15. 15.

    Digital Imaging and Communication in Medicine (DICOM)-Part 1-20: National Electrical Manufacturers Association, 2015

  16. 16.

    Digital Imaging and Communication in Medicine (DICOM)-Part 4: National Electrical Manufacturers Association, 2015

  17. 17.

    Digital Imaging and Communication in Medicine (DICOM)-Part 18: National Electrical Manufacturers Association, 2015

  18. 18.

    Koutelakis GV, Lymberopoulos DK: WADA Service: an extension of DICOM WADO service. IEEE Trans Inf Technol Biomed 13:121–130, 2009

    Article  PubMed  Google Scholar 

  19. 19.

    Valente F, Viana-Ferreira C, Costa C, Oliveira JL: A RESTful image gateway for multiple medical image repositories. Information Technology in Biomedicine, IEEE Transactions on, 16(3):356–364, 2012

  20. 20.

    Pattynama PMT: Legal aspects of cross-border teleradiology. Eur J Radiol 73:26–30, 2010

    Article  PubMed  Google Scholar 

  21. 21.

    Witting K: Health Information Exchange: Integrating the Healthcare Enterprise (IHE). In Introduction to Nursing Informatics (pp. 79–96). Springer London, 2015

  22. 22.

    IHE Radiology (RAD) Technical Framework - Revision 14.0 Volume 4 (RAD TF-4): National Extensions, IHE International, Inc. 2015. url:http://www.ihe.net/uploadedFiles/Documents/Radiology/IHE_RAD_TF_Vol4.pdf

  23. 23.

    International I: Cross-enterprise document sharing for imaging (XDS-i), 2015

    Google Scholar 

  24. 24.

    Ribeiro LS, Rodrigues RP, Costa C, Oliveira JL: Enabling outsourcing XDS for imaging on the public cloud. Stud Health Technol Inform 192:33–37, 2013

  25. 25.

    Ebbert TL: The state of teleradiology in 2003 and changes since 1999. Yale University 2006

  26. 26.

    Binkhuysen FHB, Ranschaert ER: Teleradiology: evolution and concepts. Eur J Radiol 78:205–209, 2011

    Article  Google Scholar 

  27. 27.

    Thrall JH: Teleradiology Part II. Limitations, risks, and opportunities. Radiology 244:325–328, 2007

    Article  PubMed  Google Scholar 

  28. 28.

    Bastião L, Santos M, Costa C, Silva A, Rocha N: Dicoogle statistics: analyzing efficiency and service quality of digital imaging laboratories. Springer, Heildelberg, 2013

    Google Scholar 

  29. 29.

    Santos M, Basti??o L, Costa C, Silva A, Rocha N: DICOM and clinical data mining in a small hospital PACS: a pilot study: Springer Berlin Heidelberg, 2011

  30. 30.

    Valente F, Costa C, Silva A: Dicoogle, a Pacs featuring profiled content based image retrieval. PLoS One 8, e61888, 2013

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Viana-Ferreira C, Costa C, Oliveira JL: Dicoogle relay-a cloud communications bridge for medical imaging, 2012

  32. 32.

    Viana-Ferreira C, Ferreira D, Valente F, Monteiro E, Costa C, Oliveira JL: Dicoogle mobile: a medical imaging platform for Android. Stud Health Technol Inform 180:502, 2012

    PubMed  Google Scholar 

  33. 33.

    Silva LAB, Ribeiro LS, Santos M, Neves N, Francisco D, Costa C, Oliveira JL: Normalizing heterogeneous medical imaging data to measure the impact of radiation dose. J Digit Imaging 1–13, 2015

  34. 34.

    Bastiao Silva L, Beroud L, Costa C, Oliveira JL: Medical imaging archiving: a comparison between several NoSQL solutions. In Biomedical and Health Informatics (BHI), 2014 IEEEEMBS International Conference on (pp. 65–68). IEEE. (2014, June)

  35. 35.

    Monteiro EJ, Costa C, Oliveira JL: A DICOM viewer based on web technology

  36. 36.

    Wang S, et al: An automated DICOM database capable of arbitrary data mining (including radiation dose indicators) for quality monitoring. J Digit Imaging 24:223–233, 2011

    Article  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Santos M, Bastião L, Costa C, Silva A, Rocha N: DICOM and clinical data mining in a small hospital PACS: a pilot study: Springer Berlin Heidelberg, 2011

  38. 38.

    Santos M, de Francesco S, Silva LAB, Silva A, Costa C, Rocha N: Multi vendor DICOM metadata access—a multi site hospital approach using Dicoogle, 2013

  39. 39.

    Ratib O, Rosset A, Heuberger J: Open Source software and social networks: disruptive alternatives for medical imaging. Eur J Radiol 78:259–265, 2011

    Article  PubMed  Google Scholar 

  40. 40.

    Choudhri A, Radvany M: Initial experience with a handheld device digital imaging and communications in medicine viewer: OsiriX mobile on the iPhone. J Digit Imaging 24:184–189, 2011

    Article  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Camarlinghi N, et al: Combination of computer-aided detection algorithms for automatic lung nodule identification. Int J Comput Assist Radiol Surg 7:455–464, 2012

    Article  PubMed  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Frederico Valente.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Valente, F., Silva, L.A.B., Godinho, T.M. et al. Anatomy of an Extensible Open Source PACS. J Digit Imaging 29, 284–296 (2016). https://doi.org/10.1007/s10278-015-9834-0

Download citation

Keywords

  • PACS
  • Digital Imaging and Communications in Medicine (DICOM)
  • PACS implementation
  • PACS integration
  • PACS service
  • Radiation dose
  • Software design