Implementation of a medical image file accessing system in co-allocation data grids

Yang, Chao‐Tung; Chen, Chiu-Hsiung; Yang, Ming-Feng

doi:10.1016/j.future.2010.05.013

Cited by 25 publications

(8 citation statements)

References 27 publications

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“…Previous research [11,13,22,24,25,27] shows that co-allocation can solve the data transfer problem in grid environments; these results are categorized: RAM [12,24,22], DAS, [27,13] and ARAM [28,23]. This concept is the foundation for the current study.…”

Section: Related Workmentioning

confidence: 94%

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Accessing medical image file with co-allocation HDFS in cloud

Yang

Shih

Chen

et al. 2015

Future Generation Computer Systems

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Section: Related Workmentioning

confidence: 94%

“…Current virtualization fault tolerance response plan, focusing on recovery failure, usually relies on a checkpoint/restart mechanism. However, in today's systems, node failures can often be predicted by detecting the deterioration of health conditions [22][23][24][25][26][27][28][29][30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Accessing medical image file with co-allocation HDFS in cloud

Yang

Shih

Chen

et al. 2015

Future Generation Computer Systems

Self Cite

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“…It is estimated that over 1 EB of data pertaining to medical procedures will be produced in 2016 [9]. Due to the increasing demand for more flexible PACS solutions, researchers are actively exploring state-ofthe-art paradigms and technologies such as distributed and heterogeneous computing grids [10,11], cloud computing [12], peer-to-peer networks [6], and knowledge extraction using indexing engines [13].…”

Section: Picture Archiving and Communication Systemmentioning

confidence: 99%

Anatomy of an Extensible Open Source PACS

et al. 2015

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The conception and deployment of cost effective Picture Archiving and Communication Systems (PACS) is a concern for small to medium medical imaging facilities, research environments, and developing countries' healthcare institutions. Financial constraints and the specificity of these scenarios contribute to a low adoption rate of PACS in those environments. Furthermore, with the advent of ubiquitous computing and new initiatives to improve healthcare information technologies and data sharing, such as IHE and XDS-i, a PACS must adapt quickly to changes. This paper describes Dicoogle, a software framework that enables developers and researchers to quickly prototype and deploy new functionality taking advantage of the embedded Digital Imaging and Communications in Medicine (DICOM) services. This full-fledged implementation of a PACS archive is very amenable to extension due to its plugin-based architecture and out-of-the-box functionality, which enables the exploration of large DICOM datasets and associated metadata. These characteristics make the proposed solution very interesting for prototyping, experimentation, and bridging functionality with deployed applications. Besides being an advanced mechanism for data discovery and retrieval based on DICOM object indexing, it enables the detection of inconsistencies in an institution's data and processes. Several use cases have benefited from this approach such as radiation dosage monitoring, Content-Based Image Retrieval (CBIR), and the use of the framework as support for classes targeting software engineering for clinical contexts.

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“…In data grids, data replication and consistency refer to the same data being stored in distributed sites, and kept consistent when one or more copies are modified. Grid computing is able to increase the resource usage efficiency because it could be obtained a better balance of resource utilization [4].…”

Section: Fig 1 Cloud Computingmentioning

confidence: 99%

Building a Learning Games Network in Cloud Learning Platform Based on Immigrant Education

Chen

2011

2011 International Conference on Advances in Social Networks Analysis and Mining

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As with rapid growth of the computer technology, Elearning systems usually require many hardware and software resources, There are numerous educational institutions that cannot offer such investments, and cloud learning platform is the best solution for them. This paper proposes a model of using cloud computing and learning network upon cloud-learning solutions development. The cloud-learning platform combined with different types of games is gradually noticed by people because it can enhance user learning motivation. This research has developed a Chinese language cloud-learning system for the new immigrant based on games mode, and investigated the properties of game-based cloud-learning system, expecting to help more and more new immigrants in Taiwan. The basic concept for designing the system is developing the learning games network using digital materials, which is applied to the cloud learning platform to attract the immigrant residents and assist them to improve Chinese language skills.

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Implementation of a medical image file accessing system in co-allocation data grids

Cited by 25 publications

References 27 publications

Accessing medical image file with co-allocation HDFS in cloud

Accessing medical image file with co-allocation HDFS in cloud

Anatomy of an Extensible Open Source PACS

Building a Learning Games Network in Cloud Learning Platform Based on Immigrant Education

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