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Advances in Social Sciences Research Journal – Vol. 11, No. 5
Publication Date: May 25, 2024
DOI:10.14738/assrj.115.16941.
Yordanova, M. (2024). Recent Applications of Cloud Computing in Medical Imaging: Advances in Medical Image Analysis and Storage
of Medical Imaging Data. Advances in Social Sciences Research Journal, 11(5). 267-271.
Services for Science and Education – United Kingdom
Recent Applications of Cloud Computing in Medical Imaging:
Advances in Medical Image Analysis and Storage of Medical
Imaging Data
Mariana Yordanov
Medical University in Varna, Medical College in Varna, Varna, Bulgaria
ABSTRACT
Purpose: The purpose of this article is to offer an overview of the recent
applications of cloud computing in medical imaging and their advances in the field.
It reviews existing scientific and academic literature on cloud computing-based
platforms and solutions for medical image analysis and storage of medical imaging
data. Materials and methods: This article use available scientific literature on the
applications of cloud computing in medical imaging from PubMed, Google Scholar
and ScienceDirect. Results: The review shows that interest and research in cloud
computing applications in medical imaging has increased in recent years. This has
led to new and more effective platforms and solutions for medical image analysis
and storage of medical imaging data. Innovative applications of cloud computing in
medical imaging try to address ethical and security concerns using authentication,
encryption, anonymization and access controls. Conclusions: Cloud computing
offers promising applications in medical imaging. Notwithstanding, further
research is necessary to demonstrate their effectiveness, safety and security in a
medical setting.
Keywords: Medical Imaging, Radiography, Cloud Computing, 2D – two-dimensional, 3D –
three-dimensional, AI – artificial intelligence, API – application programming interface, AR
– augmented reality, CT – computed tomography, IoT – Internet of Things, ML – machine
learning, MRI – magnetic resonance imaging, PACS – Picture Archiving and
Communication System, VR – virtual reality
BACKGROUND
Cloud computing is a “model for delivering IT resources” [1] which offers “a new paradigm for
hosting and delivering services over the Internet” [2] Leading industry providers of cloud
computing services define it as “the on-demand availability of computing resources (such as
storage and infrastructure), as services over the internet” [3] or “the delivery of computing
services—including servers, storage, databases, networking, software, analytics, and
intelligence—over the internet” [4]. The benefits of cloud computing include pay-as-you-go
access to many services from hardware to software, on-demand storage, availability and
scalability [5].
Over the last few decades, cloud computing has emerged as one of the most important and
wide-spread advancements in information technology. Its far-ranging applications have
transformed virtually all aspects of everyday life from creating and writing documents and
running business processes to communicating online and playing video games [1]. What is
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more, cloud computing has been a key driver in the development of other emerging cutting- edge technologies, such as artificial intelligence (AI) and machine learning (ML), the Internet of
Things (IoT) and big data analysis [1] and it can be integrated with the blockchain and other
solution [6].
Cloud computing provides many benefits and opportunities in the field of medicine. It enables
more efficient data storage, analysis and greater collaboration and scalability [7]. The resources
offered by cloud computing are also “extensive, easily accessible and reconfigurable” which can
provide new and better ways to “process, store, exchange, and use large quantities of medical
data” [8]. Furthermore, cloud computing delivers those benefits in a cost-effective way [9]. One
of the most successful examples of cloud computing applications in medicine was the first
clinical trial batch for a COVID-19 vaccine which was made possible thanks to “scalable cloud
data storage and computing” [10].
Cloud computing has had a transformative impact over many sectors and industries. In
healthcare, cloud computing has had a big impact on drug discovery [11] and clinical trials [12]
for example, but all in all medicine has been slower to adopt the technology [9]. As of 2015,
there were still very few practical applications of cloud computing in the medical sector.
According to a systematic literature review by Griebel et al. just 14 out of 102 research
publications showed successful applications.
Notwithstanding, the field of medical imagining has been at the forefront of cloud computing
applications in medicine and healthcare. According to Griebel et al., medical imaging was one
of the most promising and largest domains for cloud computing applications at the time of the
review. Hence, the purpose of this article is to review recent applications of cloud computing
technology in medical imaging.
MATERIALS AND METHODS
This article is a literature review of the applications of cloud computing in medical imaging. It
uses available scientific literature in this area from PubMed, Google Scholar and ScienceDirect
and it summarizes their key findings.
REVIEW RESULTS
The systematic review of Griebel et al. from 2015 looks at the applications of cloud computing
in six directions: therapy, telemedicine/teleconsultation, public health and patient self- management, hospital management and information systems, secondary use of data and
medical imaging [7]. In the time of the review, the main applications of cloud computing in
medical imaging were in “intensive image processing”, “sharing and workflows” and
“archiving” [7]. One example is the cloud computing-enabled Picture Archiving and
Communication System (PACS) used for storage of medical images as a service [7]. One specific
application is the Android-based client which can obtain patient information and images from
an Amazon virtual machine and server [7].
From 2016 to 2024, research on the uses of cloud computing for medical imaging published on
PubMed has increased. In the decade after the review by Griebel et al., new and more effective
applications of cloud computing in the field of medical imaging have been created. The uses of
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Yordanova, M. (2024). Recent Applications of Cloud Computing in Medical Imaging: Advances in Medical Image Analysis and Storage of Medical
Imaging Data. Advances in Social Sciences Research Journal, 11(5). 267-271.
URL: http://dx.doi.org/10.14738/assrj.115.16941
cloud computing in medical imaging are focused on two areas – medical image analysis and
storage and access to medical imaging data.
Table 1: Applications of cloud computing in medical imaging.
Technology Application Features
Studierfenster, a client-server
framework with a browser interface
(for example Google Chrome,
Microsoft Edge). Advanced
applications use virtual reality (VR)
and augmented reality (AR) [13]
Medical
image
analysis
Visualizing data from computed tomography (CT)
and magnetic resonance imaging (MRI) in two- dimensional (2D) and three-dimensional (3D) web
environment; calculating dice score, Hausdorff
distance and other metrics, structure outlining,
placing anatomical and other landmarks in medical
imaging data and others [13]
TOMAAT, a cloud computing
platform for medical image analysis
with an announcement service,
distributed server nodes and client
software offering with simple
interfaces using HTTP [14]
Medical
image
analysis
Medical image segmentation; diffeomorphic
deformable atlas registration; localizing landmarks;
integration with workflows; simple client interface
[14]
XCloud-pFISTA, a medical
intelligence cloud computing
platform with browser/service
architecture which transmits data
from web-based environment to a
secure data access layer [15]
MRI
processing
and analysis
Cloud computing-based single-coil and multi-coil
MRI image reconstruction; high-quality results;
decreased reconstruction time [15]
Intelligent Cloud storage gateway
which uses cache architecture with
static rules and pattern recognition
[16]
Storage and
access to
medical
imaging data
Decreased image retrieval time, decreased
communication latency, performance gains,
customizable to different healthcare institutions
[16]
GIFT-Cloud, a data platform with
central cloud server and optional
gateway servers which can be
configurated and integrated with
external software [17]
Storage and
access to
medical
imaging data
Secure storage with anonymization, confidentiality,
encryption; transfer of imaging data and results;
collaboration between healthcare providers and
institutions; automated data upload [17]
OpenID Connect, a decentralized
authentication layer to protocols
for secure authorization and access
control [18]
Storage and
access to
medical
imaging data
High level of security; repository available; ability to
share medical images; archiving; access from web- based and mobile environments; authentication and
authorization for cloud computing-based diagnostic
imaging systems; encryption; user management [18]
Bitbox, a system which can receive
and process the user requests from
a web-based application [19]
Storage and
access to
medical
imaging data
Secure data transfer from external and independent
site into a centralized server; secure exchanging
medical imaging data; registration system, file
uploader and system management [19]
The slow application of cloud computing to medical imaging and other medical fields can be
attributed to ethical concerns [8]. In cloud computing, the cloud service provider is a third party
to healthcare providers which can impact the privacy, confidentiality and security of medical
data [8]. Hence, security represents one of the biggest risks of the adoption of cloud computing
in healthcare and medicine [20]. This creates the need for defense against security breaches,
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encryption and authorized access. According to Kagadis et al. who researched the challenges
and opportunities of cloud computing in medical imaging in 2013, one of the main security risks
was the transfer of data from one cloud computing platform to another or back to the institution
[8].
Security challenges in cloud computing can be addressed using application programming
interfaces (API), classification, authentication and data encryption [20]. In recent years, new
applications of cloud computing to medical imaging use such technologies to address ethical
and security concerns. Technological innovations in information technology and cloud
computing allow new platforms and solutions to offer higher level security, data protection,
transferability and encryption. For example, OpenID Connect uses a decentralized
authentication layer in addition to protocols for secure authorization and access control to add
extra layer of security, access control, user management and encryption. GIFT-Cloud and Bitbox
also provide features such as anonymization, encryption and safe and secure transfer of
medical imaging data and results.
The increase in the level of security and encryption in new applications makes cloud computing
a very valuable option [21] for storage and access to medical imaging data and medical image
analysis. Although cloud computing-based platforms and tools have successful trials, more
research and testing are necessary to confirm their effectiveness and security for medical
imaging with patient data at scale.
CONCLUSION
This article provides a review of the recent applications of cloud computing in medical imaging.
In recent years interest and research on the uses of cloud computing in the field has increased.
This has led to new and more effective applications medical image analysis and storage and
access to medical imaging data.
All in all, cloud computing offers promising applications in medical imaging. The platforms and
solutions for medical imaging try to address the ethical and security concerns presented by
cloud computing. Notwithstanding, more research is necessary to validate the effectiveness,
security and safety of new applications in a clinical environment.
ACKNOWLEDGEMENTS
This article benefited from the technical assistance of Iliyana N. to whom I express my gratitude.
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