Building reliable and efficient data transfer and processing pipelines: Research Articles
Concurrency and Computation: Practice & Experience - Middleware for Grid Computing
MediGRID: Towards a user friendly secured grid infrastructure
Future Generation Computer Systems
Future Generation Computer Systems
Globus toolkit version 4: software for service-oriented systems
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Exploring workflow interoperability tools for neuroimaging data analysis
Proceedings of the 6th workshop on Workflows in support of large-scale science
A classification of file placement and replication methods on grids
Future Generation Computer Systems
Exploring Workflow Interoperability for Neuroimage Analysis on the SHIWA Platform
Journal of Grid Computing
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Analysis of diffusion weighted magnetic resonance images serves increasingly for non-invasive tracking of nerve fibers in the human brain, both in clinical diagnosis and basic research. Diffusion-tensor imaging (DTI) enables in-vivo research on the internal structure of the central nervous system, an estimation of the interconnection of functional areas and diagnosis of brain tumors and de-myelinating diseases. But modeling the local diffusion parameters is computationally expensive and on standard desktop computers runtimes of up to days are common. A workflow based grid implementation of the algorithm with slice-based parallelization has shown significant speedup. However, in production use, the implementation frequently delayed and even failed, discouraging the medical collaborators to take up the management of the data processing themselves. Therefore a comprehensive analysis of possible sources for errors and delays as well as their real impact in the respective infrastructure is vital to enable clinical researchers to fully exploit the benefits of the Healthgrid application. In this manuscript, we tested different implementations of the DTI analysis with respect to robustness and runtime. Based on the results, concrete application improvements as well as general suggestions for the layout and maintenance of Healthgrids are concluded.