title: An Easy Setup for Parallel Medical Image Processing: Using Taverna and ARC.
abstract: Medical image processing is known as a computationally expensive and data intensive domain. It is thus well-suited for Grid computing. However, Grid computing usually requires the applications to be designed for parallel processing, which is a challenge for medical imaging researchers in hospitals that are most often not used to this. Making parallel programming methods easier to apply can promote Grid technologies in clinical environments. Readily available, functional tools with an intuitive interface are required to really promote healthgrids. Moreover, the tools need to be well integrated with the Grid infrastructure. To facilitate the adoption of Grids in the Geneva University Hospitals we have set up a develop environment based on the Taverna workflow engine. Its usage with a medical imaging application on the hospitals' internal Grid cluster is presented in this paper.
authors: University of Geneva, Switzerland. xin.zhou@sim.hcuge.ch
authors: Xin
authors: X
authors: Zhou
authors: Hajo
authors: H
authors: Krabbenhöft
authors: Marko
authors: M
authors: Niinimäki
authors: Adrien
authors: A
authors: Depeuringe
authors: Steffen
authors: S
authors: Möller
authors: Henning
authors: H
authors: Müller
mesh_terms: D003952:Diagnostic Imaging; D007091:Image Processing, Computer-Assisted; D012984:Software