Skip to main content

MIFS: A Peer-to-Peer Medical Images Storage and Sharing System Based on Consortium Blockchain

  • Conference paper
  • First Online:
Bioinformatics Research and Applications (ISBRA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 13064))

Included in the following conference series:

  • 1737 Accesses

Abstract

As computer vision has continued to make significant breakthroughs in recent years, medical image processing has become a research hotspot. However, hospitals that generate medical images have difficulty sharing this data due to differences in information systems and centralized storage structures. As a result, researchers often have access to only a small number of samples for research.

To solve medical image resource sharing, we propose MIFS, which stores, retrieves, authorizes, and shares medical images among hospitals. MIFS proposes a peer-to-peer data storage scheme based on consortium blockchain and an authentication mechanism compatible with the consortium blockchain. On this basis, MIFS proposes a blockchain-based access control scheme and a process for retrieving, authorizing, and sharing medical images. Finally, we implemented and evaluated the system to prove the feasibility of our scheme.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Erickson, B.J., Korfiatis, P., Akkus, Z., Kline, T.L.: Machine learning for medical imaging, vol. 37(2), pp. 505–515 (2017)

    Google Scholar 

  2. Suzuki, K.: Overview of deep learning in medical imaging, vol. 10, no. 3, pp. 257–273 (2017)

    Google Scholar 

  3. Willemink, M.J., et al.: Preparing medical imaging data for machine learning, vol. 295, no. 1, pp. 4–15 (2020)

    Google Scholar 

  4. Wang, T., et al.: A review on medical imaging synthesis using deep learning and its clinical applications, vol. 22, no. 1, pp. 11–36 (2021)

    Google Scholar 

  5. Eichelberg, M., Kleber, K., Kämmerer, M.: Cybersecurity challenges for PACS and medical imaging, vol. 27, no. 8, pp. 1126–1139 (2020)

    Google Scholar 

  6. Thabit, R.: Review of medical image authentication techniques and their recent trends, vol. 80, no. 9, pp. 13 439–13 473 (2021)

    Google Scholar 

  7. Sharma, P., Jindal, R., Borah, M.D.: Blockchain technology for cloud storage: a systematic literature review, vol. 53, no. 4, pp. 89:1–89:32 (2020)

    Google Scholar 

  8. Dai, M., Zhang, S., Wang, H., Jin, S.: A low storage room requirement framework for distributed ledger in blockchain, vol. 6, pp. 22 970–22 975 (2018)

    Google Scholar 

  9. Palai, A., Vora, M., Shah, A.: Empowering light nodes in blockchains with block summarization. In: 2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS), 2018, pp. 1–5 (2018)

    Google Scholar 

  10. Huang, H.K.: PACS and imaging informatics : basic principles and applications. Hoboken, N.J, Wiley-Liss (2004)

    Google Scholar 

  11. Ke, X., Ping, H.: Research of remote image collaboration services based on PACS sharing platform (2016)

    Google Scholar 

  12. Taylor, P.J., Dargahi, T., Dehghantanha, A., Parizi, R.M., Choo, K.-K. R.: A systematic literature review of blockchain cyber security, vol. 6, no. 2, pp. 147–156 (2020)

    Google Scholar 

  13. Zheng, Q., Li, Y., Chen, P., Dong, X.: An innovative IPFS-based storage model for blockchain. In: IEEE/WIC/ACM International Conference on Web Intelligence (WI) 2018, pp. 704–708 (2018)

    Google Scholar 

  14. Swarm: storage and communication infrastructure for a self-sovereign digital society

    Google Scholar 

  15. Benet, J.: IPFS - content addressed, versioned, p2p file system (2014)

    Google Scholar 

  16. Wilkinson, S., Boshevski, T., Brandoff, J., Buterin, V.: Storj a peer-to-peer cloud storage network (2014)

    Google Scholar 

  17. Iakovidou, C., Anagnostopoulos, N., Lux, M., Christodoulou, K., Boutalis, Y., Chatzichristofis, S.A.: Composite description based on salient contours and color information for CBIR tasks, vol. 28, no. 6, pp. 3115–3129 (2019)

    Google Scholar 

  18. Plank, J., Simmerman, S., Schuman, C.: Jerasure: a library in c/c++ facilitating erasure coding for storage applications version 1.2 (2008)

    Google Scholar 

Download references

Acknowledgment

This work was supported by National Key R&D Program of China 2017YFB0202602, 2018YFC0910405, 2017YFC1311003, 2016YFC1302500, 2016YFB0200400, 2017YFB0202104; NSFC Grants U19A2067, 61772543, U1435 222, 61625202, 61272056; Science Foundation for Distinguished Young Scholars of Hunan Province (2020JJ2009); Science Foundation of Changsha kq2004010; JZ20195242029, JH20199142034, Z202069420652; The Funds of Peng Cheng Lab, State Key Laboratory of Chemo/Biosensing and Chemometrics; the Fundamental Research Funds for the Central Universities, and Guangdong Provincial Department of Science and Technology under grant No. 2016B090918122.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shaoliang Peng .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, H., Xiao, X., Zhang, X., Li, K., Peng, S. (2021). MIFS: A Peer-to-Peer Medical Images Storage and Sharing System Based on Consortium Blockchain. In: Wei, Y., Li, M., Skums, P., Cai, Z. (eds) Bioinformatics Research and Applications. ISBRA 2021. Lecture Notes in Computer Science(), vol 13064. Springer, Cham. https://doi.org/10.1007/978-3-030-91415-8_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-91415-8_29

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91414-1

  • Online ISBN: 978-3-030-91415-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics