Evidence map›Paper›PMID 33354310›Full record

ArticleJournal of healthcare engineering2020

A Lightweight Internet Sharing Scheme for Sectional Medical Images according to Existing Hospital Network Facilities and Basic Information Security Rules.

Liang Qiao, Hao Wu, Yi Wu, Wenjing Wu, Jingyi Yang, Yongjian Nian, Mingsheng Chen, Sen Bai, Hao Huang, Mingguo Qiu

Abstract read
In one paragraph

Article in Journal of healthcare engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 5G Use in Healthcare: The Future is Present.JSLS : Journal of the Society of Laparoendoscopic Surgeons
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Liang QiaoCollege of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China.ORCID 0000-0002-8982-5636
Hao WuInformation Technology Center, Army Medical University, Chongqing, China.
Yi WuCollege of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China.
Wenjing WuDepartment of Radiology, Southwest Hospital, Army Medical University, Chongqing, China.
Jingyi YangCollege of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China.
Yongjian NianCollege of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China.
Mingsheng ChenCollege of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China.
Sen BaiCollege of Big Data and Artificial Intelligence, Chongqing Institute of Engineering, Chongqing, China.
Hao HuangDepartment of Information, Army Medical Center, Chongqing, China.ORCID 0000-0002-8914-1293
Mingguo QiuCollege of Biomedical Engineering and Imaging Medicine, Army Medical University, Chongqing, China.ORCID 0000-0002-9279-7234

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the outbreak of COVID-19, large-scale telemedicine applications can play an important role in the epidemic areas or less developed areas. However, the transmission of hundreds of megabytes of Sectional Medical Images (SMIs) from hospital's Intranet to the Internet has the problems of efficiency, cost, and security. This article proposes a novel lightweight sharing scheme for permitting Internet users to quickly and safely access the SMIs from a hospital using an Internet computer anywhere but without relying on a virtual private network or another complex deployment. Methods: A four-level endpoint network penetration scheme based on the existing hospital network facilities and information security rules was proposed to realize the secure and lightweight sharing of SMIs over the Internet. A "Master-Slave" interaction to the interactive characteristics of multiplanar reconstruction and maximum/minimum/average intensity projection was designed to enhance the user experience. Finally, a prototype system was established. Results: When accessing SMIs with a data size ranging from 251.6 to 307.04 MB with 200 kBps client bandwidth (extreme test), the network response time to each interactive request remained at approximately 1 s, the original SMIs were kept in the hospital, and the deployment did not require a complex process; the imaging quality and interactive experience were recognized by radiologists. Conclusions: This solution could serve Internet medicine at a low cost and may promote the diversified development of mobile medical technology. Under the current COVID-19 epidemic situation, we expect that it could play a low-cost and high-efficiency role in remote emergency support.

Indexed as

Computer SecurityInternetAlgorithmsComputer Communication NetworksComputersCOVID-19Diagnostic ImagingEquipment DesignHospitalizationHospitalsHumansImage Processing, Computer-AssistedMedical InformaticsProgramming LanguagesRadiologyTelemedicine

Identifiers

PMID33354310
PMCPMC7737442

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.