Gridifying a Diffusion Tensor Imaging Analysis Pipeline

—Diffusion Tensor MRI (DTI) is a rather recent image acquisition modality that can help identify disease processes in nerve bundles in the brain. Due to the large and complex nature of such data, its analysis requires new and sophisticated pipelines that are more efficiently executed within a grid environment. We present our progress over the past four years in the development and porting of the DTI analysis pipeline to grids. Starting with simple jobs submitted from the command-line, we moved towards a workflow-based implementation and finally into a web service that can be accessed via web browsers by end-users. The analysis algorithms evolved from basic to state-of-the-art, currently enabling the automatic calculation of a populationspecific “atlas” where even complex brain regions are described in an anatomically correct way. Performance statistics show a clear improvement over the years, representing a mutual benefit from both a technology push and application pull.

• Type: Conference
• Year: 2010
• Where: CCGRID
• Authors: Matthan W. A. Caan, Frans M. Vos, Antoine H. C. van Kampen, Sílvia D. Olabarriaga, Lucas J. van Vliet
• Keywords: CCGRID 2010, Distributed And Parallel Computing, DTI Analysis Pipeline, Image Acquisition Modality, —diffusion Tensor Mri