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A Midas Plugin to Enable Construction of Reproducible Web-based Image Processing Pipelines

1Kitware, Inc., Carrboro, NC, USA.
2Neuro Image Research and Analysis Laboratories, Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
3Department of Electrical-Computer Engineering, University of Iowa, Iowa City, IA, USA.
Publication Date:
Volume Number:
Front Neuroinform. 2013 Dec; 7:46.
PubMed ID:
brain image processing, automated pipelines, rodent imaging, MRI, workflow processing
Appears in Collections:
R41 NS059095/NS/NINDS NIH HHS/United States
RC1 AA019211/AA/NIAAA NIH HHS/United States
P30 HD003110/HD/NICHD NIH HHS/United States
R21 MH084132/MH/NIMH NIH HHS/United States
U24 AA020022/AA/NIAAA NIH HHS/United States
P01 DA022446/DA/NIDA NIH HHS/United States
U54 EB005149/EB/NIBIB NIH HHS/United States
R43 EB016621/EB/NIBIB NIH HHS/United States
Generated Citation:
Grauer M., Reynolds P., Hoogstoel M., Budin F., Styner M., Oguz I. A Midas Plugin to Enable Construction of Reproducible Web-based Image Processing Pipelines. Front Neuroinform. 2013 Dec; 7:46. PMID: 24416016. PMCID: PMC3875239.
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Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

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