Nothing Special   »   [go: up one dir, main page]
Skip to main content

Advertisement

Springer Nature Link
Log in

Optimization of PACS Data Persistency Using Indexed Hierarchical Data

  • Published:
Journal of Digital Imaging Aims and scope Submit manuscript

Abstract

We present a new approach for the development of a data persistency layer for a Digital Imaging and Communications in Medicine (DICOM)-compliant Picture Archiving and Communications Systems employing a hierarchical database. Our approach makes use of the HDF5 hierarchical data storage standard for scientific data and overcomes limitations of hierarchical databases employing inverted indexing for secondary key management and for efficient and flexible access to data through secondary keys. This inverted indexing is achieved through a general purpose document indexing tool called Lucene. This approach was implemented and tested using real-world data against a traditional solution employing a relational database, in various store, search, and retrieval experiments performed repeatedly with different sizes of DICOM datasets. Results show that our approach outperforms the traditional solution on most of the situations, being more than 600 % faster in some cases.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

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

Similar content being viewed by others

References

  1. Acr: Acr Practice Guideline for the Performance of Screening and Diagnostic Mammography, American College of Radiology, 2008, p 1

  2. RCR: Retention and Storage of Images and Radiological Patient Data. The Royal College of Radiologists, London, 2008, p 3

    Google Scholar 

  3. BMJ: Verordnung über den Schutz vor Schäden durch Röntgenstrahlen. Bundesministerium der Justiz, 1987

  4. CFM: RESOLUÇÃO CFM Nº 1.821/07, CFM, Editor. Conselho Federal de Medicina, 2007

  5. HDFGROUP: The HDF Group - Information, Support, and Software. 2011 [cited 2012 Jun 05]; Available from: http://www.hdfgroup.org/

  6. HDFGROUP: Who uses HDF? 2011 [cited 2012 Jun 05]; Available from: http://www.hdfgroup.org/users.html

  7. Wallauer J, Macedo DDJ, Andrade R, and Von Wangenheim A. Building a national telemedicine network. IT professional 10(2):12–17, 2008

  8. Wangenheim A, Junior CLB, Wagner HM, Cavalcante C: Ways to implement large scale telemedicine: The Santa Catarina Experience. Lat Am J Telehealth 1(3):364–377, 2010

    Google Scholar 

  9. Macedo DDJ, Von Wangenheim A, Dantas M, Perantunes HGW: An architecture for DICOM medical images storage and retrieval adopting distributed file systems. Int J High Perf Syst Arch 2(2):99–106, 2009

    Google Scholar 

  10. Macedo DDJ, Capretz MAM, Prado TC, von Wangenheim A, Dantas M: An improvement of a different approach for medical image storage. 2011

  11. CLucene: CLucene - lightning fast C++ search engine. 2011 [cited 2012 Jun 05]; Available from: http://clucene.sourceforge.net/

  12. HDFGROUP: The HDF Group. Hierarchical data format version 5, 2000-2010. 2010; Available from: http://www.hdfgroup.org/HDF5

  13. Eichelberg M, Riesmeier J, Wilkens T, Hewett AJ, Barth A, Jensch P: Ten years of medical imaging standardization and prototypical implementation: The DICOM standard and the OFFIS DICOM Toolkit (DCMTK), 2004

  14. ORACLE: Oracle Database 11g DICOM Medical Image Support. 2011 [cited 2012 Jun 05]; Available from: http://www.oracle.com/technetwork/database/multimedia/overview/dicom11gr2-wp-medimgsupport-133109.pdf

  15. Rew R, Davis G: NetCDF: an interface for scientific data access. Comput Graph Appl 10(4):76–82, 1990

    Google Scholar 

  16. Erik H, Otis G, Michael MC: Lucene in action. Manning Publications Co., 2005

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

    Article  PubMed  Google Scholar 

  18. Gosink L, Shalf J, Stockinger K, Wu K, Bethel W: HDF5-FastQuery: Accelerating Complex Queries on HDF Datasets using Fast Bitmap Indices. In: Scientific and Statistical Database Management, 2006. 18th International Conference on, 2006

  19. Sahoo S, Agrawal G: Supporting XML Based High-Level Abstractions on HDF5 Datasets: A Case Study in Automatic Data Virtualization. In: Eigenmann RL, Midkiff S Eds. Languages and Compilers for High Performance Computing. Springer, Berlin, 2005, pp 922–922

  20. Folino G, Shah AA, Kransnogor N: On the storage, management and analysis of (multi) similarity for large scale protein structure datasets in the grid. in Computer-Based Medical Systems, 2009. CBMS 2009. 22nd International Symposium on, 2009

  21. Cohen S, Hurley P, Schulz KW, Barth WL, Benton B: Scientific formats for object-relational database systems: a study of suitability and performance. SIGMOD Rec 35:10–15, 2006

    Article  Google Scholar 

  22. Magnus M, Prado TC, Wangenheim Av, Macedo DDJ, Dantas MAR: A Study of NetCDF as an Approach for High Performance Medical Image Storage. Journal of Physics: Conference Series, 2012

  23. Abduljwad F, Ning W, De X: SMX/R: Efficient way of storing and managing XML documents using RDBMSs based on paths. 2010

  24. NEMA: Digital Imaging and Communications in Medicine (DICOM) Part 1: Introduction and Overview, 2011

  25. NEMA: Digital Imaging and Communications in Medicine (DICOM) Part 3: Information Object Definition, 2011

  26. NEMA: Digital Imaging and Communications in Medicine (DICOM) Part 5: Data Structures and Encoding, 2011

  27. NEMA: Digital Imaging and Communications in Medicine (DICOM) Part 4: Service Class Specifications, 2011

  28. NEMA: Digital Imaging and Communications in Medicine (DICOM) Part 8: Network Communication Support for Message Exchange, 2011

  29. NEMA: Digital Imaging and Communications in Medicine (DICOM) Part 10: Media Storage and File Format for Media Interchange, 2011

  30. Douglas K: Postgre SQL. Sams, 2005

  31. ISO/IEC: Information technology -- Database languages, in Part 1: Framework (SQL/Framework). 2008, ISO/IEC

  32. Pourma E, Folk M: Balancing Performance and Preservation Lessons learned with HDF5, 2010

  33. HDFGROUP: How is HDF5 different than HDF4? 2011 [cited 2012 Jun 05]; Available from: http://www.hdfgroup.org/h5h4-diff.html

  34. PyTables: PyTables - Getting the most *out* of your data. 2011 [cited 2012 Jun 05]; Available from: www.pytables.org/

  35. Nam B, Sussman A: Improving access to multi-dimensional self-describing scientific datasets, 2003

  36. Salton G, Wong A, Yang CS: A vector space model for automatic indexing. Commun 18(11):613–620, 1975

    Google Scholar 

  37. Maia RS, von Wangenheim A, Nobre LF: A statewide telemedicine network for public health in Brazil. 2006

  38. PostgreSQL: SQL Conformance. 2009 [cited 2012 Jun 05]; Available from: http://www.postgresql.org/docs/8.4/static/features.html

  39. Amaral E, Comunello E, Dantas MAR, Macedo DDJ: Replicação Distribuída de Imagens Médicas sob o Formato de Dados HDF5, in 8th International Information and Telecommunication Technologies Symposium 2009, I2TS: Florianópolis, SC - Brazil

  40. Lucene A: Lucene FAQ. 2011 12-2011 [cited 2012 Jun 05]; Available from: http://wiki.apache.org/lucene-java/LuceneFAQ#Why_am_I_getting_a_TooManyClauses_exception.3F

Download references

Author information

Authors and Affiliations

  1. Department of Informatics and Statistics, INE, Florianópolis, Brazil

    Thiago C. Prado, M. A. R. Dantas & Aldo von Wangenheim

  2. Post-Graduate Program in Knowledge Engineering and Management—PPGEGC, Federal University of Santa Catarina—UFSC, Florianópolis, Brazil

    Douglas D. J. de Macedo

  3. Departamento de Informática e Estatística—Sala 320, Universidade Federal de Santa Catarina—UFSC, Campus Universitário Trindade 320, 88040-900, Florianópolis, SC, Brazil

    Douglas D. J. de Macedo

Authors
  1. Thiago C. Prado
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Douglas D. J. de Macedo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. A. R. Dantas
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aldo von Wangenheim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Douglas D. J. de Macedo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Prado, T.C., de Macedo, D.D.J., Dantas, M.A.R. et al. Optimization of PACS Data Persistency Using Indexed Hierarchical Data. J Digit Imaging 27, 297–308 (2014). https://doi.org/10.1007/s10278-013-9665-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10278-013-9665-9

Keywords

Search

Navigation