Using grid technologies to face medical image analysis challenges
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Modeling service-based multimedia content adaptation in pervasive computing
Proceedings of the 1st conference on Computing frontiers
A Grid Enabled PSE for Medical Imaging: Experiences on MedIGrid
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
The Telescience Project: Application to Middleware Interaction Components
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
Context-based design of mobile applications for museums: a survey of existing practices
Proceedings of the 7th international conference on Human computer interaction with mobile devices & services
An augmented campus design for context-aware service provision
Proceedings of the 33rd annual ACM SIGUCCS conference on User services
The Telescience Tools: Version 2.0
E-SCIENCE '05 Proceedings of the First International Conference on e-Science and Grid Computing
An Agent-Based Service Network for Personal Mobile Devices
IEEE Pervasive Computing
Mobile phone based AR scene assembly
MUM '05 Proceedings of the 4th international conference on Mobile and ubiquitous multimedia
Grid-enabling medical image analysis
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid - Volume 01
A Java-based Wrapper for Wireless Communications
CISIS '08 Proceedings of the 2008 International Conference on Complex, Intelligent and Software Intensive Systems
IEEE Transactions on Information Technology in Biomedicine
Hi-index | 0.00 |
Bias artifact corrupts MRIs in such a way that the image is afflicted by illumination variations. Some of the authors proposed the exponential entropy-driven homomorphic unsharp masking (E2D-HUM) algorithm that corrects this artifact without any a priori hypothesis about the tissues or the MRI modality. Moreover, E2D-HUM does not care about the body part under examination and does not require any particular training task. People who want to use this algorithm, which isMatlab-based, have to set their own computers in order to execute it. Furthermore, they have to be Matlab-skilled to exploit all the features of the algorithm. In this paper, we propose to make such algorithm available as a service on a grid infrastructure, so that people can use it almost from everywhere, in a pervasive fashion, by means of a suitable user interface running on smartphones. The proposed solution allows physicians to use the E2D-HUM algorithm (or any other kind of algorithm, given that it is available as a service on the grid), being it remotely executed somewhere in the grid, and the results are sent back to the user's device. This way, physicians do not need to be aware of how to use Matlab to process their images. The pervasive service provision formedical image enhancement is presented, along with some experimental results obtained using smartphones connected to an existing Globus-based grid infrastructure.