Paper Info
Title
Using Dynamic Condor-Based Services for Classifying Schizophrenia in Diffusion Tensor Images
Abstract
Diffusion Tensor Imaging (DTI) provides insight into the white matter of the human brain, which is affected by Schizophrenia. By comparing a patient group to a control group, the DTI-images are on average expected to be different for white matter regions. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are used to classify the groups. In this work, the number of principal components is optimised for obtaining the minimal classification error. A robust estimate of this error is computed in a cross-validation framework, using different compositions of the data into a training and a testing set. Previously, sequential runs were performed in MATLAB, resulting in long execution times. In this paper we describe an experiment where this application was run on a grid with minimal modifications and user effort. We have adopted a service-based approach that autonomously launches Image Analysis Services onto a campus-wide Condor pool comprising of volunteer resources. This allows high throughput analysis of our data in a dynamic resource pool. The challenge in adopting such an approach comes from the nature of the resources, which change randomly with time and thus require fault tolerance. Through this approach we have reduced the computation time of each dataset from 90 minutes to less than 10. A minimal classification error of 22\% was obtained, using 15 principal components.
Year
DOI
Venue
2008
10.1109/CCGRID.2008.12
CCGrid
Keywords
Field
DocType
linear discriminant analysis,service-based approach,diffusion tensor images,principal component analysis,classifying schizophrenia,principal component,dynamic condor-based services,image analysis services,minimal classification error,computation time,campus-wide condor pool,control group,minimal modification,cross validation,fault tolerant,image analysis,sequential analysis,image classification,robustness,diffusion tensor imaging,schizophrenia,tensile stress,high throughput,robust estimator
Data mining,Diffusion MRI,MATLAB,Pattern recognition,Computer science,Robustness (computer science),Fault tolerance,Artificial intelligence,Linear discriminant analysis,Contextual image classification,Grid,Principal component analysis
Conference
Citations 
PageRank 
References 
3
0.41
19
Authors
5
Name
Order
Citations
PageRank
Simon Caton115916.20
Matthan Caan2202.77
Silvia D. Olabarriaga3657.36
Omer F. Rana42181229.52
Bruce Batchelor561.14