This work emphasizes the use of grid computing and web technology for automatic postprocessing of brain magnetic resonance images (MRI) in the context of neuropsychiatric
(Alzheimer’s disease) research. Post-acquisition image processing is achieved through the
interconnection of several individual processes into pipelines. Each process has input and output
data ports, options and execution parameters, and performs single tasks such as: a) extracting
individual image attributes (e.g. dimensions, orientation, center of mass), b) performing image
transformations (e.g. scaling, rotation, skewing, intensity standardization, linear and non-linear
registration), c) performing image statistical analyses, and d) producing the necessary quality
control images and/or files for user review. The pipelines are built to perform specific sequences of
tasks on the alphanumeric data and MRIs contained in our database.
The web application is coded in PHP and allows the creation of scripts to create, store and execute
pipelines and their instances either on our local cluster or on high-performance computing
platforms. To run an instance on an external cluster, the web application opens a communication
tunnel through which it copies the necessary files, submits the execution commands and collects
the results.
We present result on system tests for the processing of a set of 821 brain MRIs from the
Alzheimer's Disease Neuroimaging Initiative study via a nonlinear registration pipeline composed
of 10 processes. Our results show successful execution on both local and external clusters, and a 4-
fold increase in performance if using the external cluster. However, the latter’s performance does
not scale linearly as queue waiting times and execution overhead increase with the number of tasks
to be executed
