The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Decentralized autonomous imaging data processing using blockchain
Abstract
Imaging studies are one of the leading drivers of modern medical decision making, and thus, their accessibility to healthcare providers and patients is of critical importance. However, current techniques for storage and transferring medical imaging data are inconvenient and sometimes wholly inadequate. In this paper, we propose a decentralized autonomous medical image processing approach using blockchain technology. Blockchain will enable the sharing of key relevant data using a distributed, decentralized, shared ledger that is available to participants. We outline a framework that utilizes blockchain to enable users to access imaging data in a secure and autonomous manner. A user case is experimentally investigated to validate our proposed approach.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Blockchain can enable individuals to manage their health records information in such a way through which they can authorize certain entities to securely access and update their PHRs.
“Also, blockchain can enable individuals to manage their health records information in such a way through which they can authorize certain entities (e.g., patients and health institutions the authority) to securely access and update their PHRs [7], [8].”
From Blockchain for Giving Patients Control Over Their Medical Records (2020) · cites this paper as [8]
Citations
Cites
A Review on the Use of Blockchain for the Internet of Things
Fernandez-Carames, T. M., & Fraga-Lamas, P. (2018) · IEEE Access · doi:10.1109/access.2018.2842685 · Cited by 1,078
Smart contract-based access control for the internet of things
Zhang, Y., Kasahara, S., Shen, Y., Jiang, X., & Wan, J. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2847705 · Cited by 788
A Systematic Review of the Use of Blockchain in Healthcare
Hölbl, M., Kompara, M., Kamišalić, A., & Nemec Zlatolas, L. (2018) · Symmetry · doi:10.3390/sym10100470 · Cited by 780
Flagged first, then by citations
Research works printed but not linked: 12
- Wüst, 2018, Do you need a blockchain?, 45, 10.1109/CVCBT.2018.00011 · DOI
- Linn, 2016, Blockchain for health data and its potential use in health IT and health care related research, ONC/NIST Use of Blockchain for Healthcare and Research Workshop. Gaithersburg, Maryland, United States: ONC/NIST
- Ekblaw, 2016, A case study for blockchain in health-care:medrec prototype for electronic health records and medical research data, 13, 13
- Swan, 2015, O’Reilly Media, Inc., Blockchain: Blueprint for a new economy
- Maesa, 2017, Blockchain based access control, 206, 10.1007/978-3-319-59665-5_15 · DOI
- 10.1002/sec.v9.18 · DOI
- 10.5210/fm.v2i9.548 · DOI
- Lee, 2018, Implementation of IoT system using block chain with authentication and data protection, 936, 10.1109/ICOIN.2018.8343261 · DOI
- Xu, 2018, Blendcac: A blockchain-enabled decentralized capability-based access control for IoTs, 10.1109/Cybermatics_2018.2018.00191 · DOI
- 10.1117/1.OE.58.4.041609 · DOI
- Nagothu, 2018, A microservice-enabled architecture for smart surveillance using blockchain technology, arXiv preprint arXiv:1807.07487 · arXiv
- Nikouei, 2018, Real-time index authentication for event-oriented surveillance video query using blockchain, arXiv preprint arXiv:1807.06179 · arXiv
Cited by
Sorted by citations
Blockchain for Giving Patients Control Over Their Medical Records
Madine, M. M., Battah, A. A., Yaqoob, I., Salah, K., Jayaraman, R., Al-Hammadi, Y., Pesic, S., & Ellahham, S. (2020) · IEEE Access · doi:10.1109/access.2020.3032553 · Cited by 208
“Ideally, this process is automated and requires no human interaction, which is possible with the Internet of things (IoT)-enabled hardware and software components [33], [34].”
Background
Metadata
- Authors
- Yang, L., Chen, G., Xu, R., Chen, S., & Chen, Y.
- Affiliations
- Intelligent Fusion Technology (United States) (US)
- Binghamton University (US)
- Venue
- Multimodal Biomedical Imaging XIV
- Publisher
- SPIE
- Published
- 2019-02-27
- Pages
- 29
- OpenAlex
- W2915691927
- Cited by
- 14
- References
- 3
- Citations by year
- 2025: 2 · 2021: 2 · 2020: 5 · 2019: 5
- FWCI
- 2.39
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Multimodal Biomedical Imaging (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- blockchain, medical image processing, decentralized data processing, distributed ledger technology, secure data access, healthcare data storage
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
