A midas plugin to enable construction of reproducible web-based image processing pipelines

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...

Full description

Bibliographic Details
Main Authors:	Grauer, Michael, Reynolds, Patrick, Hoogstoel, Marion, Budin, Francois, Styner, Martin A., Oguz, Ipek
Format:	Online
Language:	English
Published:	Frontiers Media S.A. 2013
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3875239/

id	pubmed-3875239
recordtype	oai_dc
spelling	pubmed-38752392014-01-11 A midas plugin to enable construction of reproducible web-based image processing pipelines Grauer, Michael Reynolds, Patrick Hoogstoel, Marion Budin, Francois Styner, Martin A. Oguz, Ipek Neuroscience 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. Frontiers Media S.A. 2013-12-30 /pmc/articles/PMC3875239/ /pubmed/24416016 http://dx.doi.org/10.3389/fninf.2013.00046 Text en Copyright © 2013 Grauer, Reynolds, Hoogstoel, Budin, Styner and Oguz. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Grauer, Michael Reynolds, Patrick Hoogstoel, Marion Budin, Francois Styner, Martin A. Oguz, Ipek
spellingShingle	Grauer, Michael Reynolds, Patrick Hoogstoel, Marion Budin, Francois Styner, Martin A. Oguz, Ipek A midas plugin to enable construction of reproducible web-based image processing pipelines
author_facet	Grauer, Michael Reynolds, Patrick Hoogstoel, Marion Budin, Francois Styner, Martin A. Oguz, Ipek
author_sort	Grauer, Michael
title	A midas plugin to enable construction of reproducible web-based image processing pipelines
title_short	A midas plugin to enable construction of reproducible web-based image processing pipelines
title_full	A midas plugin to enable construction of reproducible web-based image processing pipelines
title_fullStr	A midas plugin to enable construction of reproducible web-based image processing pipelines
title_full_unstemmed	A midas plugin to enable construction of reproducible web-based image processing pipelines
title_sort	midas plugin to enable construction of reproducible web-based image processing pipelines
description	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.
publisher	Frontiers Media S.A.
publishDate	2013
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3875239/
_version_	1612042260892876800

A midas plugin to enable construction of reproducible web-based image processing pipelines

Similar Items