Grid-enabling medical image analysis

Germain, Coralie; Breton, Vincent; Clarysse, Patrick; Gaudeau, Yann; Glatard, Tristan; Jeannot, Emmanuel; Legré, Yannick; Loomis, Charles; Montagnat, Johan; Moureaux, Jean-Marie; Osorio, A.; Pennec, Xavier; Texier, Romain

doi:10.1109/ccgrid.2005.1558593

Cited by 9 publications

(9 citation statements)

References 13 publications

(14 reference statements)

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“…Although task runtime is included in their model, they did not specify how the task runtime affects the reputation. The time related performance can also be evaluated by the resource availability [4].…”

Section: B Deadlinementioning

confidence: 99%

Reputation Based Dead Line Scheduling in Grid Computing Environment

R¹

2019

International Journal of Advanced Research in Computer and Comm

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Grid is a kind of distributed and parallel computing. Mainly it is used to solve complex problems such as weather forecasting, earth observation and financial modeling (etc). Hence we propose the reputation based deadline scheduling in grid, which is to be consider important factor for resource selection. In this paper, reputation based deadline scheduling is based on select for solving a complex task within particular schedule. Most existing reputation models used for reliability evaluation ignore the time influence. Based on Reputation Prioritized Based Deadline Scheduling Algorithm (PDSA) using average turnaround time. PDSA has shown optimal performance as compared to EDF and RR scheduling algorithm.

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Section: B Deadlinementioning

confidence: 99%

Reputation Based Dead Line Scheduling in Grid Computing Environment

R¹

2019

International Journal of Advanced Research in Computer and Comm

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“…Huge computing power is already required to run advanced computational models in their direct mode (for prediction) or inverse mode (to adapt to a specific patient from biomedical measurements). The amount of required computing power to process large databases will require the development of grid-enabled algorithms capable of exploiting distributed computing power and data in large international networks [23].…”

Section: Large Distributed Databasesmentioning

confidence: 99%

Asclepios: a research project team at INRIA for the analysis and simulation of biomedical images

Ayache

Clatz

Delingette

et al. 2009

From Semantics to Computer Science

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Asclepios 1 is the name of a research project-team officially launched on November 1 st , 2005 at INRIA Sophia-Antipolis, to study the Analysis and Simulation of Biological and Medical Images. This research project-team follows a previous one, called Epidaure, initially dedicated to Medical Imaging and Robotics research. These two project teams were strongly supported by Gilles Kahn, who used to have regular scientific interactions with their members. More generally, Gilles Kahn had a unique vision of the growing importance of the interaction of the Information Technologies and Sciences with the Biological and Medical world. He was one of the originators of the creation of a specific BIO theme among the main INRIA research directions, which now regroups 16 different research teams including Asclepios, whose research objectives are described and illustrated in this article.

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“…Grid technologies are found in various healthcare applications. These include national health information sharing in Canada [Bilykha et al 2003], medical imaging analysis [Germain et al 2005], eDiaMoND for breast cancer screening and a federated database of annotated mammograms [Jirotka et al 2005], biomedical modeling . Alternative conceptualizations of using grids for data storage include the byCast grid for the BC Cancer Agency [Slik et al 2003] and Globus MEDICUS [Erberich et al 2007].…”

Section: Grid Technology In Healthcarementioning

confidence: 99%

Information Systems and Healthcare XVII: Operational Stakeholder Relationships in the Deployment of a Data Storage Grid for Clinical Image Backup and Recovery

King

2008

CAIS

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A data storage grid (DSG) is under development for a federation of clinical sites to provide a cost-effective backup and recovery solution for their clinical images. Geographic separation provides fault-tolerance against localized disasters. Pooling of storage resources across organizations utilizes economies of scale associated with storage area networks. However, the control and administration of a DSG is now spread across multiple organizations increasing the complexity of deployment. Socio-technical issues specific to a DSG arise as there are now multiple stakeholders linked together in a network of new relationships. Agreement upon every relationship is necessary to determine service level agreements, security, and liability such as in the event of a security breach. Implications of socio-technical networks and stakeholder analysis on the operators, rather than the users, of an interorganizational DSG are discussed.

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Grid-enabling medical image analysis

Cited by 9 publications

References 13 publications

Reputation Based Dead Line Scheduling in Grid Computing Environment

Reputation Based Dead Line Scheduling in Grid Computing Environment

Asclepios: a research project team at INRIA for the analysis and simulation of biomedical images

Information Systems and Healthcare XVII: Operational Stakeholder Relationships in the Deployment of a Data Storage Grid for Clinical Image Backup and Recovery

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