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Dicoogle Open Source: The Establishment of a New Paradigm in Medical Imaging

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Abstract

The rapid and continuous growth of data volume and its heterogeneity has become one of the most noticeable trends in healthcare, namely in medical imaging. This evolution led to the deployment of specialized information systems supported by the DICOM standard that enables the interoperability of distinct components, including imaging modalities, repositories, and visualization workstations. However, the complexity of these ecosystems leads to challenging learning curves and makes it time-consuming to mock and apply new ideas. Dicoogle is an extensible medical imaging archive server that emerges as a tool to overcome those challenges. Its extensible architecture allows the fast development of new advanced features or extends existent ones. It is currently a fundamental enabling technology in collaborative and telehealthcare environments, including research projects, screening programs, and teleradiology services. The framework is supported by a Learning Pack that includes a description of the web programmatic interface, a software development kit, documentation, and implementation samples. This article gives an in-depth view of the Dicoogle ecosystem, state-of-the-art contributions, and community impact. It starts by presenting an overview of its architectural concept, highlights some of the most representative research backed up by Dicoogle, some remarks obtained from its use in teaching, and worldwide usage statistics of the software. Finally, the positioning of Dicoogle in the medical imaging software field is discussed through comparison with other well-known solutions.

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Notes

  1. Online: www.dicoogle.com

  2. Available at: https://bioinformatics-ua.github.io/dicoogle-learning-pack/

  3. Jetty: https://www.eclipse.org/jetty/

  4. Dicoogle Resources: https://bioinformatics-ua.github.io/dicoogle-api

  5. https://bioinformatics-ua.github.io/dicoogle-learning-pack/docs/configuring/

  6. https://dicoogle.com/downloads

  7. Official website: https://www.bmd-software.com/

  8. PACScenter information: www.bmd-software.com/solutions/pacscenter/

  9. https://healthmanagement.org/pdf/article-download/how-to-support-a-nationalnetwork-for-covid-19-identification-in-medical-imaging-studies/hm3-v20-5may-how-tosupport-a-national-network.pdf

  10. Website: https://kafka.apache.org/

References

  1. R. M. Rad, P. Saeedi, J. Au, J. Havelock, A hybrid approach for multiple blastomeres identification in early human embryo images, Computers in biology and medicine 101 (2018) 100–111.

    Article  PubMed  Google Scholar 

  2. D. M. Dhane, M. Maity, T. Mungle, C. Bar, A. Achar, M. Kolekar, C. Chakraborty, Fuzzy spectral clustering for automated delineation ofchronic wound region using digital images, Computers in biology and medicine 89 (2017) 551–560.

    Article  Google Scholar 

  3. K. J. Dreyer, J. H. Thrall, D. S. Hirschorn, A. Mehta (Eds.), PACS,865 Springer-Verlag, New York, 2006. https://doi.org/10.1007/0-387-31070-3.

  4. H.K. Huang, PACS and imaging informatics: basic principles and applications (John Wiley & Sons, 2011)

  5. M. Ruiz, A. Julia, I. Boada, Starviewer and its comparison with other open-source DICOM viewers using a novel hierarchical evaluation framework, International journal of medical informatics 137 (2020) 104098.

    Article  PubMed  Google Scholar 

  6. O.S. Pianykh, Digital Imaging and Communications in Medicine (DICOM) - A Practical Introduction and Survival Guide (Springer, 2012). https://doi.org/10.2967/jnumed.109.064592

  7. P. Mildenberger, M. Eichelberg, E. Martin, Introduction to the DICOM standard, European Radiology 12 (4) (2002) 920–927. https://doi.org/10.1007/s003300101100.

    Article  PubMed  Google Scholar 

  8. J. M. Silva, E. Pinho, E. Monteiro, J. F. Silva, C. Costa, Controlled searching in reversibly de-identified medical imaging archives, Journalof Biomedical Informatics 77 (2018) 81 – 90

    Article  Google Scholar 

  9. P. H. Oliveira, L. C. Scabora, M. T. Cazzolato, W. D. Oliveira, R. S. Paixao, A. J. Traina, C. Traina, Employing domain indexes to efficiently query medical data from multiple repositories, IEEE journal of biomedical and health informatics 23 (6) (2018) 2220–2229.

    Article  PubMed  Google Scholar 

  10. E. Pinho, T. Godinho, F. Valente, C. Costa, A multimodal search engine for medical imaging studies, Journal of Digital Imaging 30 (1) (2017)39–48. https://doi.org/10.1007/s10278-016-9903-z.

    Article  PubMed  Google Scholar 

  11. E. Pinho, C. Costa, Extensible architecture for multimodal information retrieval in medical imaging archives, in 2016 12th International Conference on Signal-Image Technology Internet-Based Systems (SITIS), 2016,890 pp. 316–322. https://doi.org/10.1109/SITIS.2016.58.

  12. K. Fan, S. Wang, Y. Ren, H. Li, Y. Yang, Medblock: Efficient and secure medical data sharing via blockchain, Journal of medical systems 42 (8) (2018) 136.

    Article  PubMed  Google Scholar 

  13. M. Vikram, A. Anantharaman, S. BS, An approach for multimodal medical image retrieval using latent dirichlet allocation, in: Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, 2019, pp. 44–51.

  14. R. Sigal, PACS as an e-academic tool, International Congress Series 1281(2005) 900–904.900

  15. J. M. Silva, A. Guerra, J. F. Silva, E. Pinho, C. Costa, Face deidentification service for neuroimaging volumes, in: 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), IEEE, 2018, pp. 141–145.

    Google Scholar 

  16. S. Sinha, U. Sinha, H. Kangarloo, H. K. Huang, A PACS-based interactive teaching module for radiologic sciences. AJR. American journal of roentgenology 159 (1) (1992) 199–205.

    Article  CAS  PubMed  Google Scholar 

  17. C. C. Tchoyoson Lim, G. L. Yang, W. L. Nowinski, F. Hui, Medical Image Resource Center–making electronic teaching files from PACS, Journal of Digital Imaging 16 (4) (2003) 331–336.

  18. C. Lim, G. Yang, Electronic teaching files and continuing professional development in radiology., Biomedical imaging and intervention journal910 2 (2) (2006) e5. https://doi.org/10.2349/biij.2.2.e5.

  19. L. E. Wilkinson, S. R. Gledhill, An Integrated Approach to a Teaching File Linked to PACS, Journal of Digital Imaging 20 (4) (2007) 402–410. https://doi.org/10.1007/s10278-006-1045-2.

    Article  PubMed  Google Scholar 

  20. S. J. Doran, J. D'Arcy, D. J. Collins, R. Andriantsimiavona, M. Orton, D. M. Koh, M. O. Leach, Informatics in Radiology: Development of a Research PACS for Analysis of Functional Imaging Data in Clinical Research and Clinical Trials, Radio Graphics 32 (7) (2012) 2135–2150

    Google Scholar 

  21. M. Eichelberg, J. Riesmeier, T. Wilkens, A. J. Hewett, A. Barth, P. Jensch,920 Ten years of medical imaging standardization and prototypical implementation: the DICOM standard and the offis DICOM toolkit (DCMTK), in: Medical Imaging 2004: PACS and Imaging Informatics, Vol. 5371, International Society for Optics and Photonics, 2004, pp. 57–69.

  22. M. J. Warnock, C. Toland, D. Evans, B. Wallace, P. Nagy, Benefits of us925 ing the dcm4che dicom archive, Journal of Digital Imaging 20 (1) (2007)125–129.

    Article  PubMed  PubMed Central  Google Scholar 

  23. M. Woodbridge, G. Fagiolo, D. P. O’Regan, MRIdb: medical image management for biobank research, Journal of digital imaging 26 (5) (2013)886–890.930

  24. S. Jodogne, The Orthanc ecosystem for medical imaging, Journal of digital imaging 31 (3) (2018) 341–352.

    Article  PubMed  PubMed Central  Google Scholar 

  25. E. J. Gomez, F. del Pozo, E. J. Ortiz, N. Malpica, H. Rahms, A broadband multimedia collaborative system for advanced teleradiology and medical imaging diagnosis, IEEE Transactions on information technology in935 biomedicine 2 (3) (1998) 146–155.

  26. Y. S. Lim, D. D. Feng, T. W. Cai, A web-based collaborative system for medical image analysis and diagnosis., in: VIP, 2000, pp. 93–95.

  27. O. Sumtsova, T. Aikina, L. Bolsunovskaya, C. Phillips, O. Zubkova, P. Mitchell, Collaborative learning at engineering universities: Benefits and challenges, International Journal of Emerging Technologies in Learning (iJET) 13 (1) (2018) 160–177.

    Article  Google Scholar 

  28. M. C. Makel, K. N. Smith, M. T. McBee, S. J. Peters, E. M. Miller, A path to greater credibility: Large-scale collaborative education research, AERA Open 5 (4) (2019)

  29. C. Daniel, F. Macary, M. G. Rojo, J. Klossa, A. Laurinavicius, B. A. Beckwith, V. Della Mea, Recent advances in standards for collaborative digital anatomic pathology, in: Diagnostic Pathology, Vol. 6, BioMed Central, 2011, p. S17.

  30. K. Zhang, T. Ling, Y. Yang, J. Sun, M. Wang, J. Zhang, Clinical experiences of collaborative imaging diagnosis in shanghai district healthcare services, in: Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations, Vol. 9789, International Society for Optics and Photonics, 2016, p. 97890X.

  31. R. Maree, L. Rollus, B. St evens, R. Hoyoux, G. Louppe, R. Vandaele, 955 J.M. Begon, P. Kainz, P. Geurts, L. Wehenkel, Collaborative analysis of multi-gigapixel imaging data using cytomine, Bioinformatics 32 (9) (2016) 1395–1401.

  32. I. Maglogiannis, C. Andrikos, G. Rassias, P. Tsanakas, A DICOM based collaborative platform for real-time medical teleconsultation on medical960 images, in: GeNeDis 2016, Springer, 2017, pp. 79–91.

  33. D. Díaz, G. Corredor, E. Romero, A. Cruz-Roa, A web-based telepathology framework for collaborative work of pathologists to support teaching and research in latin america, in: Sipaim–Miccai Biomedical Workshop, Springer, 2018, pp. 105–112.965

  34. M. Pedrosa, J. M. Silva, J. F. Silva, S. Matos, C. Costa, Screen-dr: Collaborative platform for diabetic retinopathy, International journal of medical informatics 120 (2018) 137–146.

    Article  PubMed  Google Scholar 

  35. R. Lebre, R. Jesus, P. Nunes, C. Costa, Collaborative framework for a whole-slide image viewer, in: 2019 IEEE 32nd International Symposium970 on Computer-Based Medical Systems (CBMS), IEEE, 2019, pp. 221–224.

    Google Scholar 

  36. F. Valente, L. A. B. Silva, T. M. Godinho, C. Costa, Anatomy of an extensible open source PACS, Journal of Digital Imaging 29 (3) (2016) 284–296. https://doi.org/10.1007/s10278-015-9834-0.975

    Article  PubMed  Google Scholar 

  37. F. Valente, C. Costa, A. Silva, Dicoogle, a PACS featuring profiled content-based image retrieval, PloS one 8 (5) (2013) e61888.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. C. Costa, F. Freitas, M. Pereira, A. Silva, J. L. Oliveira, Indexing and retrieving DICOM data in disperse and unstructured archives, International Journal of Computer Assisted Radiology and Surgery 4 (1) (2009) 71–77.980. https://doi.org/10.1007/s11548-008-0269-7.

  39. T. M. Godinho, C. Viana-Ferreira, L. A. Bastião Silva, C. Costa, A routing mechanism for cloud outsourcing of medical imaging repositories, IEEE Journal of Biomedical and Health Informatics 20 (1) (2016) 367–375. https://doi.org/10.1109/JBHI.2014.2361633.985

  40. J. M. Silva, T. M. Godinho, D. Silva, C. Costa, A community-driven validation service for standard medical imaging objects, Computer Standards& Interfaces 61 (2019) 121–128.

    Article  Google Scholar 

  41. T. M. Godinho, R. Lebre, L. B. Silva, C. Costa, An efficient architecture to support digital pathology in standard medical imaging repositories, Journal of Biomedical Informatics 71 (2017) 190 – 197.

    Article  Google Scholar 

  42. E. J. M. Monteiro, F. Valente, C. Costa, J. L. Oliveira, A recommender system for medical imaging diagnostic., in: MIE, 2015, pp. 461–463.

  43. M. Santos, L. Bastiao, A. Silva, N. Rocha, DICOM metadata analysis for population characterization: A feasibility study, Procedia Computer Science 100 (2016) 355 – 361.

    Article  Google Scholar 

  44. M. Santos, L. Bastiao, C. Costa, A. Silva, N. Rocha, DICOM and clinical data mining in a small hospital PACS: A pilot study, in: M. M. Cruz Cunha, J. Varajao, P. Powell, R. Martinho (Eds.), ENTERprise Information Systems, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, pp.1000 254–263.

  45. J. Philbin, F. Prior, P. Nagy, Will the next generation of PACS be sitting on a cloud?, Journal of digital imaging 24 (2) (2011) 179–183.

    Article  PubMed  Google Scholar 

  46. T. Rostrom, C.-C. Teng, Secure communications for PACS in a cloud environment, in: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, 2011, pp. 8219–8222.

    Google Scholar 

  47. L. S. Ribeiro, C. Viana-Ferreira, J. L. Oliveira, C. Costa, XDS-I out-sourcing proxy: ensuring confidentiality while preserving interoperability, IEEE journal of biomedical and health informatics 18 (4) (2013) 1404–1412

    Article  Google Scholar 

  48. L. A. B. Silva, L. S. Ribeiro, M. Santos, N. Neves, D. Francisco, C. Costa, J. L. Oliveira, Normalizing heterogeneous medical imaging data to measure the impact of radiation dose, Journal of digital imaging 28 (6) (2015)671–683.

    Article  PubMed  PubMed Central  Google Scholar 

  49. T. M. Godinho, C. Costa, et al., Assessing the relational database model for optimization of content discovery services in medical imaging repositories, in: 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom), IEEE, 2016, pp. 1–6.

  50. S. Al-Janabi, A. Huisman, P.J. Van Diest. Digital pathology: Current status and future perspectives (2012). https://doi.org/10.1111/j.1365-2559.2011.03814.x

    Article  Google Scholar 

  51. E. Pinho, C. Costa, Automated anatomic labeling architecture for content discovery in medical imaging repositories, Journal of medical systems (8) (2018) 145.

  52. T. M. Godinho, R. Lebre, J. R. Almeida, C. Costa, ETL framework for real time business intelligence over medical imaging repositories, Journal of digital imaging (2019) 1–10.

  53. A. Almeida, F. Oliveira, R. Lebre, C. Costa, NoSQL distributed database for DICOM objects, in: 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE, 2020, pp. 1882–1885.1030

  54. T. Baptista, L. B. Silva, C. Costa, Highly scalable medical imaging repository based on Kubernetes, in: 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE, 2021, pp. 3193–3200.

  55. R. Lebre, L. B. Silva, C. Costa, A cloud-ready architecture for shared medical imaging repository, Journal of Digital Imaging 33 (6) (2020)1035 1487–1498.

  56. J. R. Almeida, T. M. Godinho, L. B. Silva, C. Costa, J. L. Oliveira, Services orchestration and workflow management in distributed medical imaging environments, in: 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), IEEE, 2018, pp. 170–175.1040

  57. K. Bjorn, Evaluation of open source medical imaging software: A case study on health technology student learning experience, Procedia Computer Science 121 (2017) 724–731.

    Article  Google Scholar 

  58. S. Wideł, A. Wideł, D. Spinczyk, Overview of available open source PACS frameworks, Studia Informatica 37 (2016) 21–30.

    Google Scholar 

  59. S. Jodogne, C. Bernard, M. Devillers, E. Lenaerts, P. Coucke, Orthanc - A lightweight, restful DICOM server for healthcare and medical research, in: 2013 IEEE 10th International Symposium on Biomedical Imaging,2013, pp. 190–193. https://doi.org/10.1109/ISBI.2013.6556444.

  60. M. Pachetti, B. Marini, F. Giudici, F. Benedetti, S. Angeletti, M. Ciccozzi, C. Masciovecchio, R. Ippodrino, D. Zella, Impact of lockdown on covid19 case fatality rate and viral mutations spread in 7 countries in europe and north america, Journal of Translational Medicine 18 (1) (2020) 1–7

    Article  Google Scholar 

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Acknowledgements

This work received support from FCT, Fundação para a Ciência e a Tecnologia, under the project UID/CEC/00127/2019 and POCI-01-0145-FEDER-016385 (NETDIAMOND). This work was also funded by IMAGE-IN (EU H2020 MSCAITN No 813920).

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Authors and Affiliations

  1. University of A Coruña, Campus de Elviña, A Coruña, Spain

    Rui Lebre & Rui Jesus

  2. University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal

    Rui Lebre & Carlos Costa

  3. BMD Software, PCI - Creative Science Park Via do Conhecimento, Aveiro, Portugal

    Eduardo Pinho, Rui Jesus & Luís Bastião

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Appendix 1

Appendix 1

Table 2 Examples of research studies conducted in the past five years
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Lebre, R., Pinho, E., Jesus, R. et al. Dicoogle Open Source: The Establishment of a New Paradigm in Medical Imaging. J Med Syst 46, 77 (2022). https://doi.org/10.1007/s10916-022-01867-3

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